Joint Machine Learning Seminars


2005-03-16 15:00: Approximating The Hierarchical Dirichelet Distribution (Phil Cowans)

2005-03-23 15:00: Bayesian Learning for Visual Inference (Ollie Williams)

2005-03-30 15:00: Communicating with buttons: current progress in one- and two-button Dasher (Ingrid Jendrzejewski)

2005-04-05 16:30: The predictive power of contractive neural-network spaces (Ashley Mills)

2005-04-11 16:00: Bloom Filters and Tries (a comparison) (David MacKay)

2005-04-20 15:00: Astronomical Image Recognition (David MacKay)

2005-04-27 15:00: Variational Gibbs Sampling (Ulrich Paquet)

2005-05-03 14:00: Computer Othello (Sanjoy Mahajan)

2005-05-11 14:00: Joint Gaussian Process-Density Mixtures (Ole Winther, DTU / Inference Group)

2005-05-17 14:00: Nested Sampling for Motif Discovery (Thomas Down, Sanger Institute)

2005-06-07 16:00: Neighbourhood Components Analysis (Sam Roweis, University of Toronto)

2005-06-08 15:00: Information and Intelligence (Alex Selby)

2005-06-08 16:30: A Tale of T9 (Cliff Kushler)

2005-06-09 09:30: Japanese Language Model (Takashi Kaburagi)

2005-06-09 15:00: Hierarchical Dirichlet Process Models for Time Series Data (Matthew Beal, SUNY at Buffalo)

2005-06-10 11:00: Language Modelling In Dasher: A Tutorial (Phil Cowans)

2005-06-10 15:30: Monte Carlo experiments in computer Go (Lukasz Lew, Vrije University, Amsterdam)

2005-06-14 14:00: Epitomes And Epitexts (Phil Cowans, Inference Group)

2005-06-15 15:00: A Fast Learning Algorithm for Deep Belief Nets (Geoffrey E. Hinton, University of Toronto)

2005-06-21 16:30: Efficient computer interfaces using continuous gestures, language models, and speech; Probabilistic methods for interpreting electronic ink (Keith Vertanen  and Phil Cowans, Cavendish Laboratory)

2005-06-22 15:00: LOCUS: Learning Object Classes with Unsupervised Segmentation (John Winn, Microsoft Research)

2005-06-29 15:00: What we face in facing up to complexity in the genetics of complex disease (Ken Weiss, Pennsylvania State University)

2005-07-03 15:00: To be confirmed (David MacKay)

2005-07-06 15:00: An introduction to Brain-Computer Interfaces (Seb Wills, Inference Group)

2005-07-22 15:00: Why do fruitflies like bananas? (Gregory Jefferis, Department of Zoology)

2005-08-03 15:00: Progress with #Dasher, a Continuous Gesture IDE (Luke Church)

2005-08-16 12:00: Efficient communication with buttons: an update on Button Dasher (Ingrid Jendrzejewski, Inference Group)

2005-08-17 12:30: Language relationships, phonology, and Greek (Tudor Dimofte, Inference Group)

2005-08-17 15:00: Adaptive Monte Carlo Methods for Simulation and Optimization (Chunlin JI, Engineering Department)

2005-10-05 15:00: Bayesian Pattern Ranking for Move Prediction in the Game of Go (David Stern, Inference Group, Cavendish Laboratory)

2005-10-12 15:00: A Cross-Entropy Based Method to Analyse Iterative Decoding (Qinglin Luo)

2005-11-02 15:00: Dasher for the blind, and some visual illusions (David MacKay, Inference Group)

2005-11-09 15:00: Monte Carlo is Bayesian (John Skilling, ex-DAMTP)

2005-11-18 14:00: Locked-in syndrome (Mick Donegan, ACE Centre Oxford)

2005-11-23 15:00: Efficient Quantum Computation with linear optics (Oliver Stegle, Inference Group)

2005-11-28 14:30: Cheap and cheerful inference machines for tracking (Ollie Williams, CUED)

2006-01-11 15:00: Eye Tracking with Consumer Hardware (Dan Witzner Hansen, IT University of Copenhagen)

2006-01-19 15:00: Lexicographic text analysis using non-negative factorisation techniques (Sinead Williamson)

2006-01-20 15:00: Recognition and prediction of biological motion (Robert Wilson, University of Pennsylvania)

2006-01-25 15:00: Dynamical Networks for Agent Systems (Pedro Ortega, Department of Computer Science, University of Chile)

2006-02-01 15:00: Latency-optimal fault-tolerant replication (Piotr Zielinski, Inference Group)

2006-02-08 15:00: Virtual-move Parallel Tempering (Ivan Coluzza, University of Cambridge)

2006-02-15 15:00: Experimental Annotation of the Human Genome (Paul Bertone, EMBL-European Bioinformatics Institute)

2006-02-16 15:15: Uncertainty Logic (Christian Steinruecken)

2006-02-22 15:00: Topic Modeling: Beyond Bag-of-Words (Hanna Wallach, Inference Group)

2006-03-01 15:00: Speech Recognition During Dictation Corrections (Keith Vertanen, Inference Group)

2006-03-07 12:30: Probabilistic Dimensional Reduction with the Gaussian Process Latent Variable Model (Dr Neil Lawrence, Computer Science, University of Sheffield)

2006-03-07 14:00: Student Project Presentations: "Redundancy in Turing machines";  "A two button implementation of Dasher" and "Relationships between energy and information in fly retina" (R.J. Henderson, Tim Ward, and Mike Baker)

2006-03-10 11:00: Student Project Presentations: "Colour Memorisation", "One button communication" and "Optimising digital fountain codes" ( J.E. Main,  Naath (Helen) Cousins,  and Olly Madge)

2006-03-13 15:00: Aggregation of Particles in Stochastic Flows (Per Sillr?n, Chalmers University, Sweden)

2006-03-22 15:00: Epitomic representation of natural signals (Anitha Kannan, Microsoft Research Cambridge)

2006-03-28 14:00: Graph Transformation Method for Calculating Waiting Times in Markov Chains (Semen Trygubenko, Department of Chemistry, University of Cambridge)

2006-03-29 15:00: Bayesian Online Changepoint Detection (Ryan Adams, Inference Group)

2006-04-13 15:00: The Swendsen-Wang algorithm (tutorial), and the "Baby and Toy" algorithm (David MacKay)

2006-04-19 15:00: Hierarchical Passage Retrieval (Phil Cowans, Inference Group)

2006-04-19 16:30: Bayesian approximation for physical inverse problems (Debasish Roy)

2006-04-21 15:00: The 'Rich Club' phenomenon in large networks (Anthony Leung, Hong Kong)

2006-04-26 14:30: Sleeping Beauty and the Armchair Cosmologist (David MacKay)

2006-05-03 14:00: The Capacity of the Deletion Channel (David MacKay)

2006-05-10 14:00: To be confirmed (David Stern, Inference Group)

2006-05-10 15:00: How to Parameterize a Positive-definite Matrix (David MacKay)

2006-05-24 14:00: Title to be confirmed (David Stern, Inference Group)

2006-05-26 14:00: Joint LDPC Decoding and Timing Recovery Using Code Constraint Feedback (Christopher Jones)

2006-05-31 14:00: Capacity of phase-based attractor networks with pairwise couplings (David MacKay)

2006-06-07 14:00: Finite element modelling of growing microtubules (Michael Verhoek, KCL)

2006-06-15 14:00: Blissymbolics (Annalu Waller, University of Dundee)

2006-06-20 14:00: A Bayesian Unfolding Method Applied to the PAMELA Experiment (Germano Percossi)

2006-06-21 14:00: In search of the brain's wiring (Philipp Hennig, Heidelberg)

2006-06-27 14:00: Blissymbolics - The Emergence of a Written Language (Annalu Waller, Dundee)

2006-06-28 11:00: Music Access for the Disabled (Jon Hall, Engineering Department)

2006-06-28 14:00: Information-Theoretic Security in Wireless Networks: From Theory to Practice (Miguel Rodrigues, Digital Technology Group, Cambridge)

2006-06-28 17:00: Ligand detection and discrimination by spatial relocalisation: the complexities of T cell activation (Nigel Burroughs (Dept of Mathematics, University of Warwick))

2006-07-05 14:00: Gaussian Process models for solving ODEs (Oliver Stegle, Inference Group)

2006-07-12 14:00: On the Analysis of Ellipsoid Approximation of Nested Sampling (Ratthachat Chatpatanasiri)

2006-07-18 14:00: Implicit learning in Music (Martin Rohrmeier,  Centre for Music and Science)

2006-07-19 14:00: Divergence measures and latent variable models (Ulrich Paquet)

2006-07-26 14:00: The Manufacture of Bioethanol - A brief Introduction (Samir Bhatt)

2006-07-26 16:00: Graphical Combinator Programming (Christian Steinruecken)

2006-08-02 14:00: sparse GP classification (Andrew Naish)

2006-08-02 14:00: neural phase codes (Bob Wilson)

2006-08-09 11:00: Cognitive Cars (K. Venkatesh Prasad, Ford Motor Company)

2006-08-09 14:00: Getting it Right the Second Time: Recognition of Spoken Corrections (Keith Vertanen, Inference Group)

2006-08-16 14:00: Naive OCR? (Seb Wills, Inference Group)

2006-08-23 14:00: How to veto anonymously under surveillance? (Piotr Zielinski, Inference Group)

2006-09-06 14:00: MCMC for doubly-intractable distributions (Iain Murray, Gatsby Computational Neuroscience Unit, UCL)

2006-09-13 14:00: An interesting preprint (David MacKay)

2006-09-20 14:00: Optimised Digital Fountain Codes for Medium Blocklengths (Oliver Madge)

2006-10-05 16:00: Mixture Models and the EM Algorithm (Professor Chris Bishop, Microsoft Research Cambridge)

2006-10-16 14:00: Leaf Selection for Maximising Diversity in a Tree (Fabio Pardi)

2006-10-18 14:00: Teaching Statistics -  A Bag of Tricks (David MacKay, Cavendish Laboratory)

2006-10-26 14:45: Dynamic imaging of blood flow in the conjunctival and episcleral microcirculations of the human eye: a new chapter in diagnostic imaging? (Dr. Paul Meyer, Ophthalmology Department, Addenbrookes Hospital)

2006-10-26 16:00: Gaussian Processes for Machine Learning (Ed Snelson, Gatsby Unit, UCL)

2006-11-08 14:00: Do Scanning Electron Microscopes have a point-spread function? (Philipp Hennig)

2006-11-09 16:00: Causality (Dr Ricardo Silva, Gatsby Unit, UCL)

2006-11-15 14:00: Vector Gaussian Processes (Ryan Adams, Inference Group)

2006-11-16 16:00: Expectation Propagation (Dr Tom Minka, Microsoft Research Cambridge)

2006-11-22 14:00: Bayesian estimation of neuronal connectivity from MEA recordings (Fabio Rigat)

2006-11-23 16:00: Advanced MCMC Methods (Iain Murray, Gatsby Unit, UCL)

2006-12-06 14:00: Transcription regulation: from parts list to genomic network. (Nicholas Luscombe)

2006-12-13 14:00: Robust Gaussian Process Regression and Applications (Oliver Stegle)

2006-12-13 14:45: Title to be confirmed (Luis Diaz-Santana, Dept of Optometry and Visual Science, City University)

2007-01-10 14:00: HMMs for controlling dynamical systems (Marcus Frean)

2007-01-17 14:00: Learning from positive and unlabeled data (Jurgen Van Gael)

2007-01-24 14:00: Modeling text with Dirichlet compound multinomial distributions (Charles Elkan, UCSD)

2007-01-31 14:00: Modeling Natural Sounds with Gaussian Modulation Cascade Processes (Rich Turner, Gatsby Computational Neuroscience Unit)

2007-02-01 16:00: Robot Localisation and Mapping (Dr Paul M Newman, Oxford University)

2007-02-14 14:00: NIPS presentations (Ryan Adams)

2007-02-21 14:00: Title to be confirmed (Giselle Walker)

2007-02-22 16:00: An Introduction to Non-parametric Bayesian Methods (Professor Zoubin Ghahramani, University of Cambridge)

2007-02-28 14:00: Some interesting data: Cryptic DNA sequence periodicities are ubiquitous, organism specific and distinguish introns from exons. (Giselle Walker)

2007-03-01 16:00: Dirichlet Processes and Hierarchical Dirichlet Processes (Dr Yee Whye Teh, Gatsby Unit, UCL)

2007-03-07 14:00: Metropolis-Coupled MCMC for Nested Sampling (Ratthachat (Jung))

2007-03-14 14:00: Gaussian Process Product Models (Ryan Adams)

2007-03-15 13:00: Logistic Regression with a Laplacian prior on the Eigenvalues: Convex duality and application to EEG classification (Ryota Tomioka (University of Tokyo / Fraunhofer FIRST))

2007-03-15 16:00: Bayesian Ranking (Ralf Herbrich, Microsoft Research Cambridge)

2007-03-21 14:00: Monte Carlo Approaches to Game Playing (David Stern, Strategic Inference Task Force, Cambridge)

2007-03-23 14:00: Logistic regression with a Laplacian prior on the singular values:  convex duality and application to EEG classification. (Ryota Tomioka (冨岡亮太), University of Tokyo / Fraunhofer FIRST IDA)

2007-03-26 14:00: Inference in Bayesian Networks using Dynamic Discretisation (Martin Neil, Agena Ltd & David Marquez, Queen Mary, University of London)

2007-03-28 14:00: Inductive Logic Programming and Kernel methods (David Kirchheimer, Bristol University)

2007-03-30 14:00: Learning Patterns in the Game of Go (Emil Nijhuis, University of Amsterdam)

2007-04-03 13:00: Analysis of Channel Coding for Redundant Sources (Joseph Boutros, ENST Paris)

2007-04-25 14:00: Context Tree Weighting (Martijn van Veen and Philip Cowans)

2007-05-02 14:00: Bayesian nonparametric latent feature models (Zoubin Ghahramani)

2007-05-09 14:00: Shape writing: fluid text entry on mobile devices (Per Ola Kristensson)

2007-05-16 14:00: Learning and Stability in Random Sigma-Pi Networks (Philip Sterne)

2007-05-28 14:00: Probabilities, Complexities and Game Semantics (Christian Steinruecken)

2007-05-30 14:00: An Error-Correcting Keyboard (Carl Scheffler, Inference Group, University of Cambridge)

2007-06-06 14:00: Open Vocabulary Confusion Networks for Speech Recognition (Keith Vertanen)

2007-06-13 14:00: Language Modelling Discussion (Phil Cowans)

2007-07-25 14:00: Minimal Perfect Hashing: hash tables with no collisions (Piotr Zielinski and others)

2007-08-29 14:00: What is a Fab Lab? (Carl Scheffler (University of Cambridge))

2007-09-12 14:00: Five energy plans for Britain (David MacKay (Cavendish Laboratory))

2007-09-13 13:00: Covariate Shift Adaptation: Supervised Learning When Training and Test Inputs Have Different Distributions (Masashi Sugiyama (Tokyo Institute of Technlogy))

2007-09-14 14:00: Geometric Algorithms for Linear Independent Component Analysis (Hao Shen, National ICT Australia and Australian National University, Canberra)

2007-09-19 14:00: Graph Kernels for Data Mining (Karsten Borgwardt, Machine Learning Group @ CUED)

2007-09-26 14:00: Shape writing: a fast and fluid writing system designed for mobile devices (Per Ola Kristensson)

2007-09-28 09:00: Coffee + mingle (.)

2007-09-28 10:00: Sequencing hundreds of humans - how to collect the data efficiently and make sense of it (Richard Durbin. Wellcome Trust Sanger Institute)

2007-09-28 10:40: Short talks about statistical machine learning (Various speakers)

2007-09-28 11:20: coffee (.)

2007-09-28 11:50: Short talks about statistical machine learning II (Various speakers)

2007-09-28 14:00: Inference in Gaussian Process models (Carl Rasmussen, Engineering)

2007-09-28 14:40: Short talks about statistical machine learning III (Various speakers)

2007-09-28 15:20: Discussion + tea (Zoubin Ghahramani, Engineering)

2007-09-28 16:30: Short talks about statistical machine learning IIII (Speaker to be confirmed)

2007-09-28 17:15: Developing a general-purpose message-passing library (Tom Minka)

2007-09-28 18:00: Mingle (.)

2007-10-03 14:00: Optimal Spreading Sequences for Chaos-Based Communication Systems; Using CSK as a Case Study (Theodore Papamarkou, University of Warwick)

2007-10-10 14:00: Improving the Power of eQTL Studies by accounting for non-genetic Factors (Oliver Stegle, University of Cambridge)

2007-10-17 14:00: Hidden Common Cause Relations in Relational Learning (Ricardo Silva (Statistical Laboratory))

2007-10-18 16:00: Group Theory and Machine Learning (Imre Risi Kondor, Gatsby Unit, UCL)

2007-10-24 14:00: Bliss-Dasher -- Efficient semantic writing with any muscle (David MacKay (Cavendish Laboratory))

2007-10-25 16:00: Spectral Clustering (Arik Azran,  Machine Learning Group)

2007-10-31 14:00: The last thing that we should talk about (David MacKay (Cavendish Laboratory))

2007-11-01 16:00: Prequential Statistics (Philip Dawid, Statistical Laboratory, Cambridge)

2007-11-07 11:30: Optimal Control and Reinforcement Learning with Gaussian Process Models (Marc Deisenroth (University of Cambridge))

2007-11-07 14:00: An overview of covariance operators in Hilbert space, and their applications (Arthur Gretton)

2007-11-14 14:00: Branch and Bound reconstruction of Balanced Minimum Evolution optimal trees (Fabio Pardi)

2007-11-15 16:00: Machine Learning Applications / Challenges in Natural Language Parsing (Ted Briscoe, Computer Laboratory)

2007-11-16 17:15: Life beyond the Physics department (Ed Ratzer (GCHQ))

2007-11-21 14:00: Clinical data based optimal STI strategies for HIV: a reinforcement learning approach (Dr Guy-Bart Stan (University of Cambridge))

2007-11-22 16:00: Error Correcting Codes (David J.C. MacKay, Department of Physics)

2007-11-26 15:00: Gene Regulatory Network Inference: A Kernel-Based Learning Approach (Sandy Klemm, University of Cambridge)

2007-11-28 14:00: The development of a motor network in Drosophila, the role of precocious neural activity in the emergence of coordination (Michael Bate (University of Cambridge))

2007-12-07 11:00: Composing: Linear and Non-Linear Thinking (Richard Burns (Cambridge Poet))

2008-01-16 14:00: NIPS presentations (Philipp Hennig (University of Cambridge))

2008-01-17 16:00: Graphical Models (Christopher M. Bishop, Microsoft Research, Cambridge)

2008-01-22 11:00: Sparse Gaussian Process in Disease Mapping (Jarno Vanhatalo, Helsinki University of Technology)

2008-01-23 14:00: Modeling Science: Topic models of Scientific Journals and Other Large Document Collections (David Blei, Computer Science, Princeton University)

2008-01-29 16:00: Reinforcement Learning (Peter Dayan, Gatsby Unit, UCL)

2008-01-30 14:00: Non-Rigid Photometric Stereo with Colored Lights (Gabriel J. Brostow (University of Cambridge))

2008-02-06 14:00: Stable distribution and data sketching (Ioana Cosma, Department of Statistics, University of Oxford)

2008-02-13 14:00: Bayesian learning of visual chunks by human observers (Dr Mate Lengyel (University of Cambridge))

2008-02-14 16:00: Information Retrieval (Stephen Robertson, Microsoft Research Cambridge)

2008-02-18 11:30: Biomedical Image Search (Alex Ksikes (University of Cambridge))

2008-02-20 14:00: Expectation Propagation, Experimental Design for the Sparse Linear Model (Matthias Seeger (Max Planck Institute for Biological Cybernetics))

2008-02-21 14:00: Model selection and model order adaptation for clustering (Peter Orbanz (ETH Zurich))

2008-02-21 16:00: Statistical Machine Translation (Bill Byrne, Machine Intelligence Laboratory)

2008-02-27 14:00: How nervous systems are designed to be energy efficient (Simon Laughlin (University of Cambridge))

2008-02-28 16:00: Inductive Logic Programming (Stephen Muggleton (Imperial College London))

2008-03-06 11:00: A Bayesian approach to network modularity: inferring the structure and scale of modular networks (Jake Hofman (Columbia University))

2008-03-11 11:30:  Discriminative Methods with Structure (Simon Lacoste-Julien (Univ of California at Berkeley))

2008-03-12 13:00: Convergence analysis of the EM algorithm and joint minimization of free energy (Dr Shin-ichi Maeda (NARA Institute of Science and Technology))

2008-03-12 14:15: (clashing event: Sustainable Energy and Arithmetic) (David MacKay)

2008-03-17 14:00: Learning quantum physics (Dr Gabor Csanyi (Dept of Engineering))

2008-03-19 14:00: On sparsity and overcompleteness in image models (Richard E. Turner (Gatsby Unit, UCL), Pietro Berkes)

2008-04-02 14:00: Beam Sampling for Infinite Hidden Markov Models (Jurgen Van Gael)

2008-04-21 11:15: Treed Gaussian Processes for Regression and Classification (Tamara Broderick (University of Cambridge))

2008-04-23 14:00: On Sparsity and Overcompleteness in Image Models (Pietro Berkes (and Richard Turner))

2008-04-25 15:00: Some models for biology (Leopold Parts)

2008-05-07 14:00: Noise in the central nervous system (Aldo Faisal)

2008-05-08 16:00: An Introduction to Statistical Learning Theory (Prof. John Shawe-Taylor (UCL))

2008-05-13 11:30: Talking with Robots: A Case Study in Architectures for Cognitive Robotics (Dr Jeremy Wyatt (University of Birmingham))

2008-05-14 14:00: Modeling Behaviour in Economic Games using Game-Theoretic POMDPs (Debajyoti Ray (Gatsby Unit, UCL))

2008-05-27 14:00: Sustainable Energy - without the hot air (David MacKay (Cavendish Laboratory))

2008-05-28 14:00: H-Infinity Clustering (Prof. Sam Roweis (Toronto))

2008-05-29 16:00: Gaussian Process Density Sampler (Ryan Prescott Adams (Inference Group, Cavendish Laboratory))

2008-05-30 11:00: Identification of dynamical subpopulations, optimal experiment design and more (Alberto Giovanni Busetto, ETH Zurich)

2008-06-12 14:00: Assessing high-dimensional latent variable models (Dr Iain Murray (Toronto))

2008-06-16 14:00: Variational inference for partially observed diffusion processes (Dr. Cedric Archambeau (University College London))

2008-06-17 11:15: Bayesian Models for Dependency Parsing Using Pitman-Yor Priors (Hanna Wallach (University of Cambridge))

2008-06-25 15:00: Bayesian analysis of complex biological systems (Dr Edo Airoldi (Princeton))

2008-07-09 16:30: The Geometry of the Space of Shapes (Prof. David Mumford (Brown University))

2008-07-15 11:30: Message-passing inference on graphical models (Simon Byrne (Cambridge))

2008-07-15 14:00: Nonparametric Bayesian Learning of Switching Dynamical Systems (Emily Fox (MIT))

2008-07-16 14:00: Modeling with Bounded Partition Functions (Ryan Prescott Adams (Inference Group, Cavendish Laboratory))

2008-07-16 14:00: Double Feature: Optimal Precoding for MIMO and Divergence Estimation for Continuous Distributions (Dr Fernando Perez-Cruz (Princeton))

2008-07-23 14:00: Semantic Texton Forests for Image Categorization and Segmentation. (Jamie Shotton, Microsoft Research Cambridge & Darwin College)

2008-07-30 14:00: From Automated Currency Validation to Protein Fold Recognition: Probabilistic Multi-class Multi-kernel Learning (Theodoros Damoulas (CS, University of Glasgow))

2008-08-13 14:00: Artificial intelligence in combinatorial game design (Cameron Browne, Queensland University of Technology)

2008-08-27 14:00: Associative Memories (Philip Sterne (University of Cambridge))

2008-09-09 14:00: Matrix Factorization and Relational Learning (Ajit Paul Singh (CMU))

2008-09-10 14:00: Non-negative matrix factorization with Gaussian process priors (Dr Mikkel N. Schmidt (Technical University of Denmark / Cambridge))

2008-09-15 14:00: Bayesian approaches to autonomous Bayesian real-time learning (Jo-Anne Ting (University of Southern California))

2008-09-16 14:00: Clustering by linear programming, convex optimization and belief propagation (Brendan Frey, University of Toronto)

2008-09-17 14:00: Nonparametric Bayesian Natural Language Model Domain Adaptation: A Hierarchical, Hierarchical Pitman-Yor Process Language Model (Dr Frank Wood (UCL))

2008-09-23 14:00: Learning Bigrams from Unigrams (Andrew B. Goldberg (University of Wisconsin, Madison))

2008-09-26 15:00: A Bayesian approach to language learning (Dr Sharon Goldwater (Edinburgh))

2008-09-29 11:00: Spoken Dialogue Management (Sebastien Bratieres)

2008-10-07 14:00: Inferring the hazard rate in change point models ( Robert Wilson, U. Penn)

2008-10-08 13:30: Shared Segmentation of Natural Scenes using Dependent Pitman-Yor Processes (Dr Erik Sudderth (UC Berkeley))

2008-10-09 16:00: Foundations of Nonparametric Bayesian Methods (Part I) (Peter Orbanz (University of Cambridge))

2008-10-16 16:00: Foundations of Nonparametric Bayesian Methods (Part II) (Peter Orbanz (University of Cambridge))

2008-10-21 15:00: Context in human robot interaction (Thomas Kollar (MIT))

2008-10-22 13:00: Efficient Sequential Monte Carlo Inference for Kingman's Coalescent (Dr Dilan Gorur (Gatsby Unit, UCL))

2008-10-22 14:15: Forensic Genomics:Kin Privacy, Driftnets and Other Open Questions (Frank Stajano, Lucia Bianchi, Pietro Liò and Douwe Korff)

2008-10-28 11:00: Foundations of Nonparametric Bayesian Methods (Part III) (Peter Orbanz (University of Cambridge))

2008-10-29 14:00: Low-cost large-scale renewable energy (Denis Bonnelle)

2008-11-12 13:00: Consensus finding, exponential models and infinite rankings (Dr Marina Meila (University of Washington))

2008-11-12 14:00: Thermochemistry and Nuclear power - Clean responsive electricity (Jonathan Lee, Trinity College)

2008-11-25 14:00: Hardness Ratios (Yue Wu)

2008-11-26 14:00: Bayesian Inductive Programming (R J Henderson (Edinburgh))

2008-11-27 16:00: Deep Networks for Vision (Prof Brendan Frey (University of Toronto))

2008-12-03 16:15: Power to Choose: How the energy choices people make will change their lives. (Dr Saul Griffith, Makani Power)

2008-12-05 11:00: Estimating the Pen Trajectories of Handwritten Static Scripts using Hidden Markov Models (Emli-Mari Nel, Vicon)

2008-12-05 14:00: Mondrian Processes (Yee Whye Teh (Gatsby Unit, UCL))

2008-12-08 10:30: Eye-Tracking in Virtual Reality ( Alessio Murgia , Reading)

2008-12-08 14:00: Visual Search: Applications and Computational Modelling (Xiao-Peng Hu, Imperial College)

2008-12-09 10:00: Optimizing  Similarity  Functions  in  Various  Pattern  Recognition  Problems (Sang Wan Lee,  KAIST Korea)

2009-01-13 14:00: HMMs for Protein Sequencing from Mass Spectrometry Data (Dr Bernd Fischer (EBI))

2009-01-19 14:00: Probabilistic Graph Models for Debugging Software (Laura Dietz (Max Planck Institute for Computer Science, Saarbrücken))

2009-01-21 13:00: The Block Diagonal Infinite Hidden Markov Model (Tom Stepleton (CMU))

2009-01-28 16:00: Parakeet: A Continuous Speech Recognition System for Mobile Touch-Screen Devices (Keith Vertanen (University of Cambridge))

2009-01-28 16:30: NIPS Highlights (Philip Sterne (University of Cambridge))

2009-01-30 13:00: Extending the Affinity Propagation Model (Inmar Givoni (University of Toronto))

2009-02-04 16:00: More NIPS highlights (Christian Steinruecken (University of Cambridge))

2009-02-17 14:00: Stochastic control as an inference problem (Prof. Bert Kappen (University of Nijmegen))

2009-02-20 11:00: Generalization in Learning (Yevgeny Seldin (Hebrew University))

2009-02-23 17:00: Bloom Filters, Related Data Structures, and their Applications (Michael Mitzenmacher (Harvard))

2009-02-24 14:00: A Survey of Results for Deletion Channels and Related Synchronization Channels (Michael Mitzenmacher, Harvard University)

2009-02-25 16:00: Dasher in Mandarin Chinese with Phonetic Pin Yin (Will Zou)

2009-02-26 16:00: An Introduction to Transcriptomics (Prof Brendan Frey (University of Toronto))

2009-03-06 15:00: Quasi-linear Sensor Management (Marco Huber (University of Karlsruhe))

2009-03-10 15:00: Shrinkage regression for multivariate inference with missing   data, with an application to portfolio balancing (Robert B. Gramacy (University of Cambridge))

2009-03-11 16:00: Painless Parse Errors (Kathryn Gray, Computer Laboratory)

2009-03-12 11:00: Cloud Ships for global warming reduction (Fred Farrell)

2009-03-12 11:30: Geothermal power in Australia (Catriona Knox)

2009-03-25 11:00: Learning from Measurements in Exponential Families (Percy Liang (University of California, Berkeley))

2009-04-15 14:00: Deducing Principles in Natural Perception (Mike Lewicki - CMU, Berlin, and Case Western)

2009-04-15 16:00: Feature tracking with full posteriors (Carl Scheffler (University of Cambridge))

2009-04-22 11:00: Literature review presentations - Tidal power, and Fuel cells (Geoffrey Supran and Colm Seeley)

2009-04-22 14:00: Bayesian periodicity detection (Tamara Broderick (University of Cambridge))

2009-04-29 14:00: Useful Computation with Coincidence Detection (Philip Sterne (University of Cambridge))

2009-05-07 16:00: Inferring building properties from temperature data (Dan Ryder-Cook)

2009-05-26 13:00: Using gradient descent for optimization and learning (Nicolas Le Roux (Microsoft Research))

2009-06-08 11:00: Inference in Models with Latent Hierarchies (Christian Steinruecken (University of Cambridge))

2009-06-12 11:00: Short ICML Practice Talk (Ryan Prescott Adams (Inference Group, Cavendish Laboratory))

2009-06-15 15:00: A quick way to learn a mixture of exponentially many linear models (Geoffrey Hinton, Canadian Institute for Advanced Research & University of Toronto)

2009-07-06 10:30: Mapping facial gestures to control cursors and switches (Emli-Mari Nel (University of Cambridge))

2009-07-08 14:00: Dashing this way and that ( Alan Lawrence (University of Cambridge))

2009-07-28 11:00: Physics Dimensions in Sage (Miriam Backens, University of Cambridge)

2009-07-28 14:00: Computable Probability Theory (Daniel Roy (MIT))

2009-08-11 15:00: Combining Collaborative Filtering with Meta Data for Scalable Recommendations (David Stern (Microsoft))

2009-08-24 11:00: Text entry performance of state of the art unconstrained handwriting recognition: a longitudinal user study (Leif Denby (University of Cambridge))

2009-08-27 11:00: Convex Variational Bayesian Inference for Large Scale Generalized Linear Models (Hannes Nickisch)

2009-09-14 11:00: Thermal expansion of beta-eucryptite (Patrick Welche (University of Cambridge))

2009-09-18 10:00: CANCELLED (Prof. Eric Xing (CMU))

2009-09-21 11:00: Capacity of Spiking Neural Networks (Philip Sterne (University of Cambridge))

2009-09-29 11:00: Of Uncertain Value -- Bayesian Quadratic Reinforcement Learning (Philipp Hennig (University of Cambridge))

2009-09-29 14:00: Coconut: Optimizing computations for machine learning (Andrew Fitzgibbon (Microsoft Research Cambridge))

2009-10-05 11:00: Recognition and Correction of Voice Web Search Queries (Keith Vertanen (University of Cambridge))

2009-10-09 13:00: Motor Skills Learning for Robotics (Jan Peters, Max Planck Institute for Biological Cybernetics in Tübingen)

2009-10-12 11:00: Learning Logical Relations (Christian Steinruecken (University of Cambridge))

2009-10-19 11:00: Inclusive user modelling (Pradipta Biswas (University of Cambridge))

2009-10-26 11:00: A facial gesture switch using hidden Markov models (Emli-Mari Nel (University of Cambridge))

2009-10-28 11:00: Information theoretic model selection in clustering (Joachim M Buhmann, Department of Computer Science, ETH Zurich)

2009-10-30 14:00: Association mapping and prediction of complex structured phenotypes (Oliver Stegle (Max Planck Institutes, Tübingen))

2009-11-02 11:00: Optimizing Dasher for the iPhone (Alan Lawrence  (University of Cambridge))

2009-11-10 11:00: KL control theory and decision making under uncertainty (Bert Kappen ( Radboud University Nijmegen, The Netherlands))

2009-11-16 11:00: 研究の紹介 (Christian Steinruecken (University of Cambridge))

2009-11-19 14:00: Gaussian Processes for Active Data Selection, Faults, Changepoints and Sensor Selection (Prof. Stephen Roberts (Oxford))

2009-11-20 14:00: Indian Buffet Processes with Power-law Behaviour (Yee Whye Teh (Gatsby Unit, UCL))

2009-11-23 11:00: Probabilistic feature tracking with non-probabilistic techniques (Carl Scheffler (University of Cambridge))

2009-11-30 11:00: Face Recognition: Who's That Blonde? (Ulrich Paquet (Imense))

2009-11-30 11:40: NIPS poster (Philipp Hennig (University of Cambridge))

2009-12-02 11:00: Joint imputation and estimation of haplotype transition probabilities (Wolfgang Lehrach, Microsoft Research Cambridge)

2009-12-04 11:00: Optimal Tag Sets for Automatic Image Annotation (Sean Moran (Edinburgh))

2010-01-11 11:00: Title to be confirmed (Dr Per Ola Kristensson (University of Cambridge))

2010-01-14 10:00: Machine Learning Course (4F13) (Zoubin Ghahramani and Carl Rasmussen (Cambridge))

2010-01-18 10:00: Visuospatial Reasoning (Stephanie Chan (MIT))

2010-01-19 11:00: CANCELLED: Learning Components for Human Sensing (Dr Fernando de la Torre (CMU))

2010-01-20 10:00: Machine Learning Course (4F13) (Zoubin Ghahramani and Carl Rasmussen (Cambridge))

2010-01-21 16:00: Accelerated Bayesian inference in cosmology (Dr. Mike Hobson (Cambridge))

2010-02-01 11:00: NIPS 2009 highlights (Philipp Hennig (University of Cambridge), Carl Scheffler (University of Cambridge))

2010-02-02 11:00: Mind Reading by Machine Learning: Optimal Experimental Design (Neil Houlsby (CUED))

2010-02-08 11:00: Automatic Selection of Recognition Errors by Respeaking the Intended Text (Keith Vertanen (University of Cambridge))

2010-02-22 11:00: Dasher (Patrick Welche (University of Cambridge))

2010-03-01 11:00: Latent Force Models with Gaussian Processes (Dr Neil Lawrence (University of Manchester))

2010-03-08 11:00: Neurally-inspired Computing (Philip Sterne (University of Cambridge))

2010-03-08 16:00: Stochastic Outlier Selection (Jeroen Janssens (Tilburg University  / University of Cambridge))

2010-03-09 11:00: Bayesian Inference in Networks of Queues (Dr Charles Sutton (Edinburgh))

2010-03-10 11:00: Title to be confirmed (Alex Davies (ANU))

2010-03-10 11:30: Subspace Codes for Adversarial Error-Correction in Network Coding (Azadeh Khaleghi (University of Toronto))

2010-03-10 12:30: Recursive CRFs for Scalable Vision (David Duvenaud (UBC))

2010-03-11 11:00: Making Sense of Data - A Research Agenda (Prof Bob Williamson (ANU and Scientific Director of NICTA))

2010-03-11 14:00: Dynamic Network Tomography: Model, Algorithm, Theory, and Application (Prof. Eric Xing (CMU))

2010-03-15 11:00: Bayesian feature tracking and head pose estimation (Carl Scheffler (University of Cambridge))

2010-03-16 11:00: Slice sampling with latent Gaussian models (Dr Iain Murray (Toronto / Edinburgh))

2010-03-22 11:00: Language Modelling with PPM (Alan Lawrence (University of Cambridge))

2010-03-29 11:00: Speech Dasher: Fast Writing using Speech and Gaze (Keith Vertanen, University of Cambridge)

2010-05-03 11:00: Report from CHI 2010 (Dr Per Ola Kristensson (University of Cambridge))

2010-05-10 11:00: Coherent Inference on Optimal Play in Games (Philipp Hennig (University of Cambridge))

2010-05-17 11:00: Ticker: A text-entry interface with audio feedback for single-switch users (Emli-Mari Nel (University of Cambridge))

2010-05-24 11:00: Conditional Counting: Approximate Multinomial Probit Regression (Philipp Hennig (University of Cambridge))

2010-05-31 11:00: Robust Associative memory (Philip Sterne (University of Cambridge))

2010-06-09 14:00: Parametric Bandits, Query Learning, and the Haystack Dimension (Prof. Michael Kearns (University of Pennsylvania))

2010-06-10 11:30: Structured Prediction Cascades (Dr. Ben Taskar (University of Pennsylvania))

2010-06-11 11:00: Message Passing In Centralized Database (Konstantina Palla (Edinburgh))

2010-06-11 14:00: Using topic models to help cure cancer (Prof Quaid Morris (Toronto))

2010-06-14 09:00: The AEGIS project (Patrick Welche (University of Cambridge))

2010-06-15 11:00: Sparse Factor Analysis Applied to Three Biological Problems (Barbara Engelhardt (University of Chicago))

2010-06-16 11:00: Natural Conjugate Gradient Learning for Fixed-Form Variational Bayes (Dr Antti Honkela (Aalto University School of Science and Technology, Finland))

2010-06-21 11:00: Differential Privacy and Probabilistic Inference (Oliver Williams (Microsoft Research))

2010-06-28 11:00: Intelligently Aiding Human-Guided Correction of Speech Recognition (Keith Vertanen (University of Cambridge))

2010-07-05 11:00: Bayesian head pose estimation (Carl Scheffler (University of Cambridge))

2010-07-07 11:00: Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design (Andreas Krause (Caltech))

2010-07-12 11:30: Using transformed domains to sparsify Gaussian Processes (Dr Miguel Lázaro-Gredilla (Universidad Carlos III de Madrid))

2010-07-16 11:00: Dasher on a Space-filling curve (Alan Lawrence (University of Cambridge))

2010-07-19 11:00: Introduction to Geometric Algebra (Patrick Welche (University of Cambridge))

2010-07-20 14:00: Scalable Parallel Computing with CUDA (James Balfour (NVIDIA))

2010-07-21 11:00: Learning Common Grammar from Multilingual Corpus / Online Multiscale Dynamic Topic Models (Dr. Tomoharu Iwata (NTT))

2010-07-26 11:00: Approximate Inference for the Loss-Calibrated Bayesian (Simon Lacoste-Julien (University of Cambridge))

2010-07-26 15:00: Efficient Bayesian analysis of multiple changepoint models (Prof Paul Fearnhead (Lancaster))

2010-07-28 14:00: Creating structured and flexible models: some  open problems (Prof Andrew Gelman (Columbia University))

2010-07-29 16:30: Culture wars, voting and polarization: divisions and unities in modern American politics (Prof Andrew Gelman (Columbia University))

2010-08-02 14:15: Some Uses of Hashing in Networking Problems (Michael Mitzenmacher, Harvard University)

2010-08-03 11:00:  Information Asymmetries in Pay-Per-Bid Auctions: How Swoopo Makes Bank (Prof Michael Mitzenmacher - Computer Science, Harvard)

2010-08-09 11:00: Topic Models -- and how to break them (Philipp Hennig (University of Cambridge))

2010-08-16 11:00: Title to be confirmed (Laurence Aitchison (University of Cambridge))

2010-08-23 11:00: Statistical Language Modelling (Carl Scheffler (University of Cambridge))

2010-08-25 14:00: On the Equivalence of Graph Cuts and Max-product Belief Propagation (Danny Tarlow (University of Toronto))

2010-08-30 11:00: Research adventures in Japan (Christian Steinruecken (University of Cambridge))

2010-09-06 11:00: Ticker: Case Study (Emli-Mari Nel (University of Cambridge))

2010-09-13 11:00: Title to be confirmed (Dr Per Ola Kristensson (University of Cambridge))

2010-09-20 11:00: Bayesian Inference with Kernels (Dr Arthur Gretton (UCL))

2010-09-30 11:00: Searching for Knowledge Instead of Web Pages (Gjergji Kasneci (Microsoft Research, Cambridge))

2010-10-04 11:00: Continuous Gesture Recognition and Visualization (Leif Denby (University of Cambridge))

2010-10-11 11:00: Bayesian Psychometry (Philipp Hennig (University of Cambridge))

2010-10-25 11:00: Putting Some Language Back Into Language Modelling (Carl Scheffler (University of Cambridge))

2010-10-27 11:30: STORM below the localisation limit (Susan Cox, Kings College London)

2010-11-01 11:00: The Multiscale Composite Dirichlet Process and its applications (Christian Steinruecken (University of Cambridge))

2010-11-05 13:30: Short talks: Mixed Cumulative Distribution Networks; Nonparametric Bayesian community discovery in social networks; Expectation Propagation for Dirichlet Process Mixture Models (Charles Blundell, Lloyd Elliot and Vinayak Rao, Gatsby Unit, UCL)

2010-11-08 11:00: South Africa's Involvement With Square Kilometre Array Bid: Infrastructure and Electromagnetic Quietness (Prof. Howard Reader, University of Stellenbosch)

2010-11-11 11:00: CANCELLED (Dr Paolo Emilio Barbano (DAMTP))

2010-11-15 11:00: Out-of-band Language Modelling (Alan Lawrence (University of Cambridge))

2010-11-18 11:00: Crowdsourcing data modelling (Anthony Goldbloom (Kaggle))

2010-11-26 11:00: Non-Smooth-Norm Image Reconstruction from Noisy Data (Dr Paolo Emilio Barbano (DAMTP, University of Cambridge))

2010-11-29 11:45: Title to be confirmed (Patrick Welche (University of Cambridge))

2010-11-30 11:00: Learning item trees for collaborative filtering with implicit feedback (Dr Andriy Mnih (Gatsby Unit, UCL))

2010-12-06 11:00: Introduction to Geometric Algebra II (Patrick Welche (University of Cambridge))

2010-12-13 11:15: A New Machine Learning Library (Christian Steinruecken (University of Cambridge))

2011-01-13 11:00: Novi Quadrianto (Novi Quadrianto, Australian National University)

2011-01-17 11:00: Machine learning in cancer research (a.k.a CRI meets CUED) (Dr Florian Markowetz (CRUK)  - lab visit)

2011-01-18 11:00: Universal Bayesian Agents: Theory and Applications (Prof. Marcus Hutter (ANU))

2011-01-25 11:00: Mining viral datasets (Dr Simon Frost (University of Cambridge))

2011-02-01 11:00: Differential Geometric MCMC Methods (Prof. Mark Girolami (UCL))

2011-02-07 11:00: A computer-vision based facial gesture switch (Emli-Mari Nel (University of Cambridge))

2011-02-25 11:00: Title to be confirmed (Yee Whye Teh (Gatsby Unit, UCL))

2011-03-04 10:30: Probabilistic matrix factorization for reconstruction of missing data (Dr Alexander Ilin (Aalto University))

2011-03-04 11:30: Expectation Propagation in Sparse Linear Models with Spike and Slab Priors (Dr José Miguel Hernández Lobato (Univ. Aut. Madrid))

2011-03-10 12:00: Challenges in implementing the Bayesian paradigm (Prof. Steve MacEachern (Ohio State))

2011-03-14 11:00: CRH: a Central Reference Handling system (Christian Steinruecken (University of Cambridge))

2011-03-15 11:00: Exponential Conditional Volatility Models (Prof Andrew Harvey (Economics, Cambridge))

2011-03-21 11:00: Rigid body motion in conformal geometric algebra (Patrick Welche (University of Cambridge))

2011-03-21 11:00: Nonlinear Dynamics of Learning (Prof. Max Welling (UC Irvine))

2011-04-11 11:00: Mandarin Dasher (Alan Lawrence (University of Cambridge))

2011-04-11 11:00: Characterization of the Ewens-Pitman family of random partitions by a deletion property and a de Finetti-type theorem for exchangeable hierarchies (Chris Haulk (UC Berkeley))

2011-05-16 11:00: Hierarchical hidden Markov models revisited (Emli-Mari Nel (University of Cambridge))

2011-05-24 11:00: An FX trading system using adaptive reinforcement learning (Professor Michael Dempster (Statistical Laboratory))

2011-06-03 11:00: Censored Exploration in Dark Pools (Prof. Michael Kearns (University of Pennsylvania))

2011-06-07 11:00: An FX trading system using adaptive reinforcement learning (Professor Michael Dempster (Statistical Laboratory))

2011-06-21 14:30: Bayesian regression and classification with multivariate sparsifying priors (Prof. Tom Heskes (Radboud University Nijmegen))

2011-07-04 11:00: Graphical Models for Bandit Problems (Kareem Amin (University of Pennsylvania))

2011-07-11 11:00: Beyond Keyword Search: Discovering Relevant Scientific Literature (Khalid El-Arini (Carnegie Mellon University))

2011-07-13 11:00: Some Practical Reflections on Graphical Models (Dr Charles Sutton (University of Edinburgh))

2011-07-28 11:30: Approximate Bayesian Inference for Large Scale Inverse Problems: A Computational Viewpoint (Prof. Matthias Seeger (EPFL))

2011-09-16 11:00: Exclusive Pólya Urns and their applications (Christian Steinruecken (University of Cambridge))

2011-09-19 15:00: Optimal Reinforcement Learning for Gaussian Systems (Philipp Hennig, Max Planck Institute for Intelligent Systems, Department of Empirical Inference, Tübingen, Germany)

2011-09-27 11:00: Factored Shapes and Appearances for Parts-based Object Understanding AND Transformation Equivariant Boltzmann Machines (Chris Williams, School of Informatics, University of Edinburgh)

2011-10-07 11:00: Machine Learning Markets (Dr Amos Storkey (Edinburgh))

2011-10-11 11:30: Bayesian Nonparametrics: Latent Feature and Prediction Models, and Efficient Inference (Piyush Rai (University of Utah))

2011-10-12 11:00: Not so naive Bayesian classification (Prof. Geoff Webb (Monash Univ))

2011-10-26 11:00: Variational Inference for Non-Conjugate Models (Dr Guillaume Bouchard (Xerox))

2011-11-16 15:00: A Maximum Entropy Perspective on Spectral Dimensionality Reduction (Prof Neil Lawrence (Sheffield))

2011-11-23 11:00: Efficient MCMC for Continuous Time Discrete State Systems (Vinayak Rao (UCL))

2011-11-28 11:00: Bayesian Quadrature for Prediction and Optimisation (Michael Osborne ( Oxford University))

2011-12-07 11:00: Scaling Machine Learning for the Internet (Prof. Alexander Smola (Yahoo!))

2012-02-20 16:00: Introduction to information theory (David MacKay (Cavendish Laboratory))

2012-02-23 12:30: Probabilistic computing: computation as universal stochastic inference, not deterministic calculation (Vikash K. Mansinghka (MIT))

2012-02-27 14:30: Entropy and data compression (I) (David MacKay (Cavendish Laboratory))

2012-03-05 14:30: Entropy and data compression (II) (David MacKay (Cavendish Laboratory))

2012-03-15 11:00: Infinite Structured Explicit Duration Hidden Markov Models (Jonathan Huggins (Columbia University))

2012-04-16 14:30: Entropy and data compression (III) (David MacKay (Cavendish Laboratory))

2012-04-23 14:30: Entropy and data compression (IV) (David MacKay (Cavendish Laboratory))

2012-04-30 14:30: Communication over noisy channels (I) (David MacKay (Cavendish Laboratory))

2012-05-02 11:15: Non-parametric Bayesian Method and Maximum-A-Posteriori Inference in Statistical Machine Translation (Tsuyoshi Okita (Dublin City University))

2012-05-04 11:15: Past work and future interests: respectively, the scattering of Anyons and Monte Carlo methods (Alexander Matthews)

2012-05-07 14:30: Communication over noisy channels (II) (David MacKay (Cavendish Laboratory))

2012-05-08 11:00: Learning with nonparametric dependence and divergence estimation (Barnabas Poczos (Carnegie Mellon University))

2012-05-21 14:30: Communication over noisy channels (III) (David MacKay (Cavendish Laboratory))

2012-05-28 14:30: An Introduction to Statistical Inference, Data Modelling & Pattern Recogntion (David MacKay (Cavendish Laboratory))

2012-06-11 14:30: Approximating Probability Distributions (I)-(II): Monte Carlo Methods and Variational Inference (David MacKay (Cavendish Laboratory))

2012-06-19 11:00: Discovery of Complex Behaviors through Contact-Invariant Optimization (Igor Mordatch (University of Washington))

2012-06-25 14:30: Advanced Monte Carlo Methods and Variational Inference (David MacKay (Cavendish Laboratory))

2012-07-03 11:00: Structured Prediction using Linear Programming Relaxations (David Sontag (NYU))

2012-07-04 11:00: Non-parametric Bayesian Learning of User Preferences: Elicitation, Sparsification and Beyond (Edwin Bonilla (NICTA/ANU))

2012-07-04 14:00: Fast Gaussian process learning for regression, semi-supervised classification, and multiway analysis (Prof Alan Qi (Purdue U))

2012-07-09 14:30: Approximating Probability Distributions (IV): Variational Methods (David MacKay (Cavendish Laboratory))

2012-07-16 14:30: Data Modelling With Neural Networks (II):  Content-Addressable Memories And  State-Of-The-Art Error-Correcting Codes (David MacKay (Cavendish Laboratory))

2012-07-27 11:00: Human Behavior Classification with Infinite Hidden Conditional Random Fields (Konstantinos Bousmalis and Stefanos Zafeiriou (Imperial College))

2012-08-03 14:00: Thermodynamics as a Theory of Decision-Making with Information Processing Costs (Pedro Ortega (Max Planck Institute for Intelligent Systems))

2012-08-08 14:00: Deep learning for vision: a case study for visual textures,  and some thoughts on a general framework (Prof. Chris Williams ( School of Informatics, University of Edinburgh))

2012-08-24 11:00: Frank-Wolfe optimization insights in machine learning (Simon Lacoste-Julien (INRIA, ENS, Paris))

2012-09-12 16:00: Efficient Sampling with Kernel Herding (Yutian Chen (University of California at Irvine) - talk given by videolink)

2012-09-24 11:00: Multi-Label Learning with Millions of Categories (Manik Varma (Microsoft Research India))

2012-09-25 15:00: Convergent and Scalable Algorithms for Expectation Propagation Approximate Bayesian Inference (Matthias Seeger, EPFL)

2012-09-26 11:00: Compressed Sensing Applications in Functional Magnetic Resonance Imaging (Christine Law (Oxford University))

2012-10-16 16:00: Distributed, Real-Time Bayesian Learning in Online Services (Ralf Herbrich (Facebook))

2012-10-22 11:00: Probabilistic methods for biomolecular structure simulations (Jes Frellsen (University of Copenhagen))

2012-10-25 14:30: Identification of causal effects (Nevena Lazic)

2012-11-15 11:30: Learning of Milky Way Model Parameters Using Matrix-variate Data in a New Gaussian Process-based Method (Dr Dalia Chakrabarty (University of Warwick))

2012-11-20 13:00: The combinatorial structure underlying a beta processes is that of a continuum of Blackwell-MacQueen urn schemes (Dr Daniel Roy (University of Cambridge))

2013-01-30 11:00: Structural Expectation Propagation (SEP): Bayesian structure learning for networks with latent variables  (Nevena Lazic (Microsoft Research Cambridge))

2013-02-22 11:00: Modelling Reciprocating Relationships with Hawkes Processes (Charles Blundell (Gatsby Unit, UCL))

2013-02-27 11:30: Feature allocations, probability functions, and paintboxes (Tamara Broderick (UC Berkeley))

2013-03-08 11:00: Using Context and Insight for the Analysis of LittleData? (Philipp Moritz (U Cambridge))

2013-03-11 11:30: An application of HDP And IBP for stream-based action recognition and high dimensional data (Ava Bargi : University of Technology, Sydney)

2013-03-25 11:00: Fast Variational Inference in the Conjugate Exponential Family (James Hensman, The Sheffield Institute for Translational Neuroscience)

2013-04-08 11:00: Non-parametric Bayesian Chromatin State Segmentation  (Will Allen (University of Cambridge and MRC-LMB))

2013-04-15 11:00: Bayesian nonparametric methods for non-exchangeable data (Nick Foti (Dartmouth College))

2013-04-30 11:00: Approaches to statistical modeling of network data (Maxim Nazarov (Bocconi University))

2013-05-01 15:00: Deep Gaussian Processes (Prof. Neil Lawrence (Sheffield))

2013-05-09 16:00: Matrix Concentration Inequalities via the Method of Exchangeable Pairs (Professor Michael I Jordan (UC Berkeley))

2013-05-22 10:20: Google's Approach to Building Relationships with Universities: Presentation and Talk by Dr David J Harper (Dr David J Harper )

2013-06-06 13:00: The combinatorial structure of conditionally i.i.d. negative binomial processes directed by a beta process (Creighton Heaukulani (University of Cambridge))

2013-07-01 11:00: Applied statistical genetics and next-generation association studies (Dr. Eleftheria Zeggini and Dr Ioanna Tachmazidou (Sanger Institute))

2013-07-01 11:00: Applied statistical genetics and next-generation association studies (Dr. Eleftheria Zeggini and Dr Ioanna Tachmazidou (Sanger Institute))

2013-07-31 14:00: Recursive Deep Learning for Modeling Semantic Compositionality (Richard Socher -  Stanford University)

2013-08-02 11:00: Annealing Between Distributions by Averaging Moments (Chris Maddison (U Toronto))

2013-08-06 11:00: Higher Order Learning for Classification in Emergency Situations (Hannah Pauline Keiler (Columbia University and DIMACS))

2013-08-08 11:00: Non-Parametric Conditional Random Fields in Computer Vision and Image Processing (Jeremy Jancsary (Microsoft Research Cambridge))

2013-09-13 11:00: Clustering Based on Predictive Variances in Gaussian Process Regression Models (Dr Hyun-Chul Kim )

2013-09-27 11:00: CANCELLED: Local Deep Kernel Learning for Efficient Non-linear SVM Prediction (Manik Varma (Microsoft Research India))

2013-10-10 11:00: Dissecting genotype to phenotype relationships (Oliver Stegle (EMBL-European Bioinformatics Institute))

2013-10-11 12:00: Nonparametric Bayesian statistics with exchangeable random structures (Daniel Roy)

2013-11-06 13:30: Contrastive Learning Using Spectral Methods (James Zou (Harvard))

2014-01-10 11:00: Sparse discriminative latent characteristics for predicting cancer drug sensitivity (David Knowles (Stanford University))

2014-01-15 11:00: Anglican; Particle MCMC inference for Probabilistic Programs (Jan-Willem van de Meent (Columbia University))

2014-01-23 15:00: Probabilistic Data Structures and Algorithms (Christian Steinruecken (University of Cambridge), Alexandre Khae Wu Navarro (University of Cambridge))

2014-02-03 11:00: Frequentist coverage of adaptive nonparametric  Bayesian credible sets (Botond Szabo (Eindhoven University of Technology))

2014-02-12 11:00: Probabilistic machine learning for knowledge extraction from videos and text (Kevin Murphy (Google))

2014-02-17 11:00: Bayesian Nonparametric Model for Power Disaggregation (Isabel Valera (University Carlos III in Madrid))

2014-02-20 10:00: Bayesian nonparametrics: Dependency and Constraint Modeling (Changyou Chen (ANU))

2014-02-21 14:00: Particle filters and curse of dimensionality (Patrick Rebeschini (Princeton))

2014-02-24 11:00: Generative probabilistic programming: applications and new ideas (Yura Perov (Oxford))

2014-02-25 09:00: Cambridge - Tuebingen PhD Applicant Talks (via Skype) (Speaker to be confirmed)

2014-02-28 11:00: Bayesian canonical correlation analysis (Seppo Virtanen (Aalto University))

2014-02-28 12:00: Parameter estimation in deep learning architectures: Two new insights. (Prof. Nando de Freitas (Oxford))

2014-03-04 11:00: Bayesian nonparametric dynamic-clustering and genetic imputation (Lloyd Elliott (Gatsby Unit, UCL / Oxford))

2014-03-11 11:00: Learning to Learn for Structured Sparsity (Nino Shervashidze (INRIA))

2014-03-14 16:00: Alpha-Stable Poisson-Kingman Processes: Some Applications and Methodologies (Yee Whye Teh, University of Oxford)

2014-03-17 11:30: Matrix Means, Distances, Kernels, and Geometric Optimization (Suvrit Sra (Max-Planck Institute for Intelligent Systems and CMU))

2014-03-28 11:00: Policy Evaluation with Temporal Differences (Christoph Dann (Technische Universität Darmstadt))

2014-04-02 11:00: Machine Learning and Order Book Dynamics (Tristan Fletcher )

2014-04-02 13:30: Probabilistic computing for Bayesian inference (Vikash K. Mansinghka (MIT))

2014-04-04 11:00: Probabilistic computing applications: BayesDB and stochastic digital circuits (Vikash K. Mansinghka (MIT))

2014-05-08 11:00: Stable Poisson-Kingman species sampling priors generated by general ordered size biased generalized gamma mixing distributions  (Prof. Lancelot James (HKUST))

2014-05-14 11:00: Density Estimation in Infinite Dimensional Exponential Families (Bharath Sriperumbudur (University of Cambridge))

2014-05-16 10:30: Bayesian inference for integer-valued Lévy processes with Non-Gaussian Ornstein-Uhlenbeck volatility modelling (Andrea Cremaschi (Kent))

2014-05-20 11:00: Practical Machine Learning at Facebook. Examples and Lessons Learnt. (Joaquin Quinonero Candela (Facebook))

2014-06-02 11:00: Unifying logic and probability: A "New Dawn" for Artificial Intelligence? (Professor Stuart Russell (UC Berkeley))

2014-06-03 11:00: Bayesian monitoring for the Comprehensive Nuclear-Test-Ban Treaty (Professor Stuart Russell (UC Berkeley))

2014-06-10 11:00: Active Learning of Linear Embeddings for Gaussian Processes (Roman Garnett, University of Bonn)

2014-07-01 11:00: Scalable Deep Gaussian Processes (James Hensman (University of Sheffield))

2014-07-02 11:00: Implicit Representation Networks (David Barber (University College London))

2014-07-16 11:00: Gaussian process regression on graphs (Peter Sollich (King's College London))

2014-08-11 11:00: On the Bethe approximation (Adrian Weller (Columbia University))

2014-09-11 11:00: Probabilistic Numerics - a snapshot of an emerging community (Philipp Hennig (Max Planck Institute for Intelligent Systems, Tübingen))

2014-09-12 11:00: Unsupervised Many-to-many Object Matching (Dr Tomoharu Iwata (NTT))

2014-09-17 11:00: Local Deep Kernel Learning for Efficient Non-linear SVM Prediction (Manik Varma (Microsoft Research India))

2014-09-24 11:00: A marginal sampler for σ-Stable Poisson-Kingman mixture models (Maria Lomeli-Garcia (Gatsby Unit, UCL))

2014-09-25 11:00: New Methods in Bayesian Optimization for Machine Learning (Jasper Snoek (Harvard University))

2014-10-21 14:30: Optimal control and optimal sampling: A statistical physics perspective. (Bert Kappen, Radboud University Nijmegen, and UCL London)

2014-10-23 14:00: A Tutorial on Probabilistic Programming (Prof. Frank Wood (Oxford))

2014-11-14 11:00: Bayesian modeling for high-level real nursing activity recognition using accelerometers (Prof. Naonori Ueda (Director Machine Learning and Data Science, NTT Labs))

2014-11-26 11:00: Oracle Variational Inference (James McInerney (Columbia University))

2014-11-28 10:30: Machine Translation with LSTMs (Ilya Sutskever (Google))

2014-12-15 10:00: The Blended Paradigm:  A Bayesian Approach to Handling Outliers and Misspecified Models  (Prof. Steven MacEachern (Ohio State University))

2015-01-23 11:00: Experiments with Non-parametric Topic Models (Prof. Wray Buntine (Monash University))

2015-01-29 12:00: Latent Branching Trees (Dr Theodore Kypraios (University of Nottingham))

2015-02-11 11:00: Orthologous networks in biological systems (Dr Christopher Penfold (Warwick))

2015-02-24 11:00: A* Sampling (Chris Maddison  (U Toronto))

2015-03-02 11:00: Probabilistic approaches to understanding bird conversations (Dan Stowell (Queen Mary University of London))

2015-03-04 11:00: Population Inference for Functional Brain Connectivity (Genevera I. Allen (Rice University))

2015-03-12 11:00: An introduction to the Mondrian Process (Matej Balog (Oxford))

2015-03-19 11:00: Evolutionary dynamics in a continuous public goods game (Matthias Bauer )

2015-04-15 11:00: Inference for infinite mixture models and Gaussian Process mixtures of experts using simple approximate MAP Inference (Alexis Boukouvalas (Aston University))

2015-04-23 11:00: Title to be confirmed (Tuan Anh Le (Oxford))

2015-04-30 11:00: Machine Learning for Quantitative Finance: A collaboration between the Cambridge Machine Learning Group and Cambridge Capital Management (Creighton Heaukulani, Matt Hoffman, Zoubin Ghahramani, and Andrew Baxter, )

2015-05-06 11:00: Direction-Only Optimisation for Neural Networks (Mark Rowland (Cambridge))

2015-05-12 11:00: Probabilistic numerics: treating numerical computation as learning, or; it's Bayes all the way down (Michael Osborne (Oxford University))

2015-06-02 11:00: Do Deep Nets Really Need to be Deep? (Dr Rich Caruana (Microsoft))

2015-06-08 17:00: Mean Field Approaches to Two Sequential Decision Making Problems. (Ramki Gummadi)

2015-06-09 11:00: Structural Markov laws / Geometry and HMC (Dr Simon Byrne)

2015-06-16 11:00: Unsupervised Learning with Latent Variable Models (Zhenwen Dai)

2015-06-18 11:00: Unsupervised Learning with Latent Variable Models (Zhenwen Dai)

2015-06-24 11:00: Random Function Classes for Machine Learning (Prof. Alex Smola (CMU))

2015-06-25 11:00: Deep Learning (Professor Geoffrey Hinton FRS (U. Toronto and Google))

2015-06-29 11:00: Deep Gaussian processes and variational propagation of uncertainty (Andreas Damianou - Sheffield University)

2015-06-29 15:00: Explaining Non-Linear Classifier Decisions with application to Deep Learning (Prof Klaus-Robert Müller (TU Berlin))

2015-06-30 11:00: Random Function Classes for Machine Learning (Prof Alexander Smola, Carnegie Mellon University)

2015-07-01 11:00: Convex and non-convex worlds in machine learning (Anna Choromanska (New York University))

2015-07-02 11:00: Extreme Classification: A New Paradigm for Ranking & Recommendation (Manik Varma (Microsoft Research India))

2015-07-03 12:30: Modeling Confounding by Half-Sibling Regression (Prof Bernhard Schölkopf (MPI Tuebingen))

2015-07-16 11:00: A new MCMC hybrid scheme for Poisson-Kingman Bayesian Nonparametric mixture models (Maria Lomeli-Garcia, UCL)

2015-07-17 11:00: Rich Component Analysis (James Zou (Microsoft Research New England))

2015-07-20 11:00: Gradient-based hyperparameter optimization through reversible learning (Dr David Duvenaud (Harvard))

2015-07-27 15:00: MCMC for non-linear state space models using ensembles of latent sequences (Alex Shestopaloff (University of Toronto))

2015-07-29 11:00: Scalable Gaussian Processes for Scientific Discovery (Dr Andrew Wilson, Carnegie Mellon University)

2015-08-27 15:00: The limits of MAP inference by MWSS on perfect graphs (Dr Adrian Weller (MLG, University of Cambridge))

2015-09-07 11:00: Information-Theoretic Bounded Rationality (Pedro A. Ortega (University of Pennsylvania))

2015-09-09 11:00: Training and Understanding Deep Neural Networks for Robotics, Design, and Perception (Jason Yosinski (Cornell))

2015-09-10 11:00: Belief and Truth in Hypothesised Behaviours (Stefano V. Albrecht -  School of Informatics at The University of Edinburgh)

2015-09-14 11:00: Convex Factorization Machines (Mathieu Blondel (NTT Communication Science Laboratorie))

2015-09-14 12:00: A-Star Sampling Review (Chris Maddison  (U Toronto))

2015-09-15 10:30: Higher Order Fused Regularization for Supervised Learning with Grouped Parameters (Koh Takeuchi (NTT Communication Science Laboratories))

2015-09-16 11:00:  Harmonic Exponential Families and Group-Equivariant Convolution Networks (Taco Cohen (University of Amsterdam))

2015-09-25 11:00: Efficient multi-task Gaussian process models for genome-wide association studies (Francesco Paolo Casale, European Bioinformatics Institute)

2015-10-14 11:00: Efficient Inference and Learning with Intractable Posteriors? Yes, Please. (Diederik P. Kingma (University of Amsterdam))

2015-10-15 11:00: Meta-Bayesian Analysis (Prof. Daniel Roy (University of Toronto))

2015-11-11 12:00: Inference of a partially observed kinetic Ising model (Dr Yasser Roudi (Kavli Inst, Trondheim & Inst for Advanced Study, Princeton))

2015-12-16 11:00: General Reinforcement Learning (Jan Leike (Australian National University))

2016-02-19 11:30: A more Automated Statistician (David Janz, Oxford University)

2016-03-09 14:00: The geometry of uncertainty (Fabio Cuzzolin, Head of AI and vision, Oxford Brookes University)

2016-03-14 09:00: Day1: Information, Inference, and Energy: A Symposium to celebrate the work of Professor Sir David MacKay FRS (See event web page)

2016-03-15 09:00: Day2: Information, Inference, and Energy: A Symposium to celebrate the work of Professor Sir David MacKay FRS (See event web page)

2016-03-16 14:00: Unsupervised Risk Estimation with only Structural Assumptions (Jacob Steinhardt (Stanford University))

2016-04-05 11:00: Inference and Learning in the Anglican Probabilistic Programming System (Jan-Willem van de Meent (Oxford))

2016-05-13 11:00: MLE-Struct: Bethe Learning of Graphical Models (Kui Tang, Columbia University)

2016-05-24 14:00: Sum-Product Networks for Probabilistic Modeling (Robert Peharz (TU Graz))

2016-05-27 11:00: Towards Weaker Supervision and Simpler Pipelines in Speech Recognition  (Gabriel Synnaeve)

2016-06-02 09:30: Turing: Rejuvenating Probabilistic Programming in Julia (Hong Ge (University of Cambridge))

2016-06-02 10:30: Novel MCMC and SMC schemes for Poisson-Kingman Bayesian Nonparametric mixture models (Maria Lomeli (University of Cambridge))

2016-06-02 11:30: Variational inference for scalable Gaussian process approximations (Alexander Matthews (University of Cambridge))

2016-06-03 14:00: Automated Reasoning and AI for Large Formal Mathematics (Josef Urban)

2016-06-07 09:30: Approximation strategies for structure learning in Bayesian networks  (Teppo Niinimäki (Helsinki))

2016-06-07 10:30: Developments in Exact Inference in Graphical Models (Stephen Pasteris (UCL))

2016-06-09 11:00: Modeling the Dynamics of Online Learning Activity (Isabel Valera )

2016-06-14 10:00: Distributed stochastic optimization for deep learning (Sixin Zhang (NYU))

2016-06-14 11:00: Learning Task Relations in Multi-Task Learning (Yu Zhang (Hong Kong University of Science and Technology))

2016-06-14 15:00: A modular architecture for Unicode text compression (Adam Gleave (University of Cambridge))

2016-07-12 11:00: Scaling and Generalizing Approximate Bayesian Inference (Prof. David Blei (Columbia University))

2016-07-21 11:00: Structured Dynamic Graphical Models & Scaling Multivariate Time Series Methodology (Professor Mike West (Statistical Science, Duke University))

2016-07-25 11:00: Discriminative Embeddings of Latent Variable Models for Structured Data (Prof Le Song (Georgia Tech))

2016-07-29 11:00: Interpretable and interactive machine learning (Dr Been Kim)

2016-08-08 11:00: Inference as Learning (George Papamakarios (University of Edinburgh))

2016-09-02 11:00: Data Driven Discrete Time Modeling of Continuous Time Nonlinear Systems: Problems, Challenges, Success Stories (Johan Schoukens, Vrije Universiteit Brussel)

2016-09-08 11:00: Learning with Memory Embeddings (Professor Volker Tresp (Ludwig Maximilian University of Munich))

2016-09-12 11:00: Dynamic Models for Health Data (Professor Katherine A Heller (Duke University))

2016-09-13 11:00: Multiresolution Matrix Factorization (Prof Risi Kondor (U Chicago))

2016-10-06 11:00: Moment matching for latent variable models: from ICA to LDA and CCA (Professor Francis Bach (INRIA, ENS))

2016-10-20 10:00: Probabilistic modeling for position and orientation estimation using inertial sensors (Manon Kok, Department of Electrical Engineering, Linköping University)

2016-11-02 11:00: Robots learning on the move: deep learning from lots of demonstration (Dushyant Rao, Oxford Robotics Institute)

2016-11-03 11:00: Multi-view Anomaly Detection via Robust Probabilistic Latent Variable Models  (Tomoharu Iwata - Learning and Intelligent Systems Research Group of NTT Communication Science Laboratories, Kyoto, Japan)

2016-11-07 11:00: A talk in two parts: (1) AI Neuroscience: How much do deep neural networks understand about the images they classify? (2) Robots that can adapt like animals.  (Prof. Jeff Clune (U Wyoming))

2016-11-17 11:00: Probabilistic Numerical Computation: A New Concept? (Prof. Mark Girolami (University of Warwick))

2016-11-22 11:30: Rejection Sampling Variational Inference (Francisco J. R. Ruiz (Columbia University & University of Cambridge))

2016-11-24 11:00: A tale of P-matrices and TripleSpinners - the unreasonable effectiveness of structured models in nonlinear embeddings (Krzysztof Choromanski, Google NY)

2016-12-01 11:00: Learning with limited supervision (Stefano Ermon, Stanford)

2016-12-13 11:00: Variational autoencoders with latent graphical models (Prof David Duvenaud (University of Toronto))

2016-12-14 15:00: Hierarchical Multi-Agent Reinforcement Learning through Communicative Actions for Human-Robot Collaboration (Elena Corina Grigore (Yale University))

2016-12-15 11:00: Bayesian optimality and frequentist extended admissibility are equivalent in saturated models (Daniel Roy (University of Toronto))

2017-01-24 11:00: Julia: Introduction and new developments (Dr Simon Byrne (Julia Computing))

2017-01-25 15:00: Variational Bayes In Private Settings (Mijung Park, University of Amsterdam)

2017-01-31 13:30: Deep Learning Book - Meeting 1 - Deep Feedforward NNs (Group Discussion)

2017-02-07 13:30: Deep Learning Book - Meeting 2 - Regularization (Group Discussion)

2017-02-10 11:00: Bayesian optimisation in many dimensions with bespoke probabilistic programs (Valentin Dalibart)

2017-02-14 13:30: Deep Learning Book - Meeting 3 - Optimization (Group Discussion)

2017-02-23 13:30: Deep Learning Book - Meeting 4 - Convolutional Networks (Group Discussion)

2017-02-23 15:00: Cooperative Inverse Reinforcement Learning (Dylan Hadfield-Menell, UC Berkeley)

2017-03-02 13:30: Deep Learning Book - Meeting 5 - ResNets and DenseNets (Group Discussion)

2017-03-09 13:30: Differential Privacy Tutorial (Alex Matthews and John Bradshaw, University of Cambridge)

2017-03-10 11:00: Control, inference and learning (Prof. dr. H.J. (Bert) Kappen (Radboud University Nijmegen))

2017-03-14 11:00: Differentially Private Bayesian Learning (Dr Antti Honkela, University of Helsinki)

2017-03-14 13:30: Deep Learning Book - Meeting 6 - Recurrent Neural Networks (Group Discussion)

2017-03-15 11:00: Bayesian Optimization for Probabilistic Programs (Tom Rainforth, University of Oxford)

2017-03-21 13:30: Deep Learning Book - Meeting 7 - Neural Turing Machines & Conditional Random Fields as RNNs (Group Discussion)

2017-04-04 13:30: Deep Learning Book - Meeting 8 - Autoencoders (Group Discussion)

2017-04-11 13:30: Deep Learning Book - Meeting 9 - Representation Learning (Group Discussion)

2017-05-25 11:00: On Different Distances Between Distributions and Generative Adversarial Networks (Martin Arjovsky)

2017-07-03 11:00: Future technology: machine learning using memristors networks (Francesco Caravelli (LANL))

2017-07-03 11:00: Future technology: machine learning using memristors networks (Francesco Caravelli (LANL))

2017-07-06 11:00: A simple neural network module for relational reasoning (David Barrett, DeepMind)

2017-07-20 14:00: Understanding Black-box Predictions via Influence Functions (Pang Wei Koh, Stanford University)

2017-09-08 11:00: Accelerating computation of SVM and DNN by binary approximation (Hironobu Fujiyoshi (Chubu University) )

2017-09-08 11:00: Towards User-Friendly Image Inpainting: Learning-to-Rank based Image Quality Assessment for Image Inpainting (Mariko Isogawa (NTT Media Intelligence Laboratories) )

2017-09-08 11:00: Deep learning for autonomous driving  (Takayoshi Yamashita (Chubu University) )

2017-09-12 11:00:  The Grammar Variational Autoencoder & Counterfactual Fairness (Dr Matt Kusner)

2017-09-14 11:00: Unbiased Estimation of the Eigenvalues of Large Implicit Matrices (Professor Ryan Adams, Princeton)

2017-09-26 15:00: A Bayesian Treatment for Uncertainty -- and its application in health care  (Dr Cheng Zhang)

2017-10-13 14:00: Transfer Learning for NLP (Sebastian Ruder, INSIGHT Centre)

2017-10-19 11:00: Nonlinear ICA using temporal structure: a principled framework for unsupervised deep learning (Prof. Aapo Hyvarinen)

2017-11-01 11:00: Targeted Disclosure to Support Auditing and Accountability for Automated Decision-making (Joshua Kroll)

2017-11-17 11:00: Towards true end-to-end learning & optimization (Dr Frank Hutter)

2017-11-24 11:00: Learning to Learn without Gradient Descent by Gradient Descent (Yutian Chen, DeepMind)

2017-11-27 11:00: Backprop through the Void: Optimizing Control Variates for Black-Box Gradient Estimation. (Geoff Roeder (University of Toronto))

2017-12-01 11:00: AI for Inclusive Finance (Alan Qi and Le Song)

2017-12-13 11:00: Bayesian Generative Adversarial Networks (Professor Andrew Wilson, Cornell University)

2017-12-13 13:30: Variational inference for some models with Polya-Gamma latent variables and Gaussian process priors (Manfred Opper, TU Berlin)

2018-02-16 11:00: Lipschitz Global Optimization (Professor Yaroslav D Sergeyev, Universita della Calabria)

2018-03-06 11:00: Structure in tensor-variate data: a trivial byproduct of simpler phenomena? (John P. Cunningham)

2018-04-15 11:00: Algorithmic Glass Ceiling in Social Networks (Ana Stoica, Columbia University)

2018-04-17 11:00: A Bayesian Perspective on Generalization and SGD (Dr. Samuel L. Smith, Google Brain)

2018-05-09 11:00: Algorithmic Glass Ceiling in Social Networks (Ana Stoica, Columbia University)

2018-05-23 11:30: Semi-Generative Modelling: Domain Adaptation with Cause and Effect Features (Julius von Kugelgen)

2018-06-14 11:00: Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness (Prof. Michael Kearns (University of Pennsylvania))

2018-06-21 11:00: Structured deep models: Deep learning on graphs and beyond (Thomas Kipf (Uni of Amsterdam))

2018-07-04 11:00: Variance in Policy Gradient methods and Learning Sequential Latent Variable Models (George Tucker, Google Brain)

2018-07-16 11:00: Fast yet Simple Natural-Gradient Variational Inference in Complex Models (Emtiyaz Khan, team leader (equivalent to Full Professor) at the RIKEN center for Advanced Intelligence Project (AIP) in Tokyo)

2018-08-24 11:00: Constraint-based causal Discovery from NOnstationary/heterogeneous Data (CD-NOD) (Biwei Huang, CMU)

2018-09-10 11:00: Interpretability - the myth, questions, and some answers (Been Kim, Google Brain)

2018-10-11 11:00: Causal Inference for Treatment Effects: A Theory and Associated Learning Algorithms (Mihaela van der Schaar )

2018-12-18 10:30: Gaussian processes for inferring latent functions in complex data models (Martin Tegner)

2019-01-17 11:00: Fairness for Sequential Decision Making Algorithms (Hoda Heidari)

2019-01-25 11:00: Observation and Intervention Incentives in Causal Influence Diagrams: Towards an Understanding of Powerful Machine Learning Systems (Tom Everitt (DeepMind))

2019-01-31 13:30: Gauge Equivariant Convolutional Networks on Manifolds (Taco Cohen)

2019-02-01 12:30: High-dimensional dynamics of generalization error in neural networks: implications for experience replay (Dr. Andrew Saxe, University of Oxford)

2019-02-14 11:00: Online Meta-Learning (Massimiliano Pontil, University College London)

2019-02-20 13:45: Generative models for few-shot prediction tasks (Marta Garnelo (Google DeepMind))

2019-03-14 14:00: The K-FAC method for neural network optimization (James Martens, Google Deep Mind)

2019-03-27 11:00: Robust machine learning for causal inference in health care (David Sontag, MIT)

2019-04-04 16:00: Global model explainability via aggregation (Umang Bhatt, CMU)

2019-04-08 11:00: NeVAE: A Deep Generative Model for Molecular Graphs (Abir De, Max Planck Institute for Software Systems)

2019-05-07 11:00: Nonparametric Generative Modeling via Optimal Transport and Diffusions with Provable Guarantees (Umut Şimşekli, Télécom Paristech)

2019-05-17 11:00: Why Do We Need New Hardware & Software for Machine Intelligence? (Victoria Rege, Scott Griffiths)

2019-06-11 15:00: Information Consumption on Social Media: Efficiency, Trust, and Divisiveness (Reza Babaei)

2019-06-20 11:00: Deep Neural Networks: A Nonparametric Bayesian Approach with Local Competition (Konstantinos P. Panousis)

2019-06-26 11:00: Learning via Data Compression: Bayesian Coresets and Sparse Variational Inference (Trevor Campbell, University of British Columbia)

2019-07-12 11:00: Efficiency and Transferability of Neural Networks (Amos Storkey, School of Informatics, University of Edinburgh)

2019-07-17 14:00: Semi-Unsupervised Learning with Deep Generative Models / Disentangling Improves VAEs' Robustness to Adversarial Attacks (Matthew Willetts and Alexander Camuto, University of Oxford / Alan Turing Institute)

2019-08-23 11:00: Two Approximate Sampling Methods for Bayesian Deep Learning (Wesley Maddox (New York University))

2019-09-04 11:00: Rotation Invariant Householder Parameterization for Bayesian PCA (Rajbir Nirwan, Goethe University, Frankfurt)

2019-09-24 10:00: Learning-Algorithms from Bayesian Principles (Emti Khan, RIKEN center for Advanced Intelligence Project)

2019-10-25 11:00: Explaining Neural Networks: Post-hoc and Natural Language Explanations (Oana Camburu, University of Oxford)

2019-10-28 11:00: Constructing temporal latent spaces: Representation learning for clustering and imputation on time series (Vincent Fortuin, ETH Zurich)

2019-10-30 10:00: Reinforcement Learning at Huawei: Robustness, Safety, and Efficiency (Haitham Ammar, Huawei)

2019-11-12 11:00: Models and inference for temporal Gaussian processes (William Wilkinson, Aalto University, Finland)

2020-01-24 11:00: Robust Deep Learning Under Distribution Shift (Zack Lipton, CMU)

2020-03-05 11:00: Game Playing Meets Game Theory: Strategic Learning from Simulated Play (wellman@umich.edu)

2020-07-22 11:00: Efficient and Structured Uncertainty: Challenges and Opportunities (Andrey Malinin, Yandex Research)

2022-04-21 11:00: Graph neural network approach for decentralized multi-robot coordination (University of Cambridge)

2022-05-13 11:30: Beyond Conformal Prediction: Distribution-Free Uncertainty Quantification for Complex Machine Learning Tasks (Anastasios Angelopoulos, PhD student at UC Berkeley)

2022-06-16 11:00: Estimating RSV seasonality from pandemic disruptions: a modelling study (Fabienne Krauer, The London School of Hygiene & Tropical Medicine)

2022-06-28 11:00: Noise-Aware Differentially Private Synthetic Data (Antti Honkela, University of Helsinki)

2022-11-14 13:00: Presenting Hawk-Eye’s Skeletrack: Our machine learning approach to building a real time skeletal tracking system for sports, and how we're using it to shape the future of fan engagement  (Lachan Thorpe, Hawk-Eye Innovations)

2022-11-17 11:00: Deep Reinforcement Learning for Multi-Agent Interaction  (Stefano Albrecht, Edinburgh)

2022-11-22 11:00: Gaussian processes, spectral analysis kernels and optimal transport (Felipe Tobar, Universidad de Chile)

2022-11-24 11:30: Measuring Alignment Between Perceptual Systems: An Analysis Through The Lens of Shared Invariances (Vedant Nanda, MPI-SWS + University of Maryland )

2022-12-15 11:00: Scalable simulation and inference in non-Gaussian stochastic PDEs (David Duvenaud (University of Toronto))

2023-01-30 11:00: Calls to F the Algorithm: Lessons from the 2020 Exam Debacle (Roger Taylor, former Chair of Ofqual)

2023-05-11 11:00: Convergence bounds for the Random Walk Metropolis algorithm - Perspectives from Isoperimetry (Sam Power, University of Bristol)

2023-07-14 11:00: Compositional mathematics and automatic gradient descent (Jeremy Bernstein, MIT)

2023-09-14 15:00: Visit and talk by Jay McClelland: "Some thoughts on the differences between human and machine intelligence" (Jay McClelland, Stanford University )

2023-11-28 11:00: Modern Bayesian Experimental Design (Dr Tom Rainforth, OxCSML Group in the Department of Statistics at the University of Oxford)

2024-02-23 13:00: Consistent Validation for Predictive Methods in Spatial Settings (David Burt, MIT)

2024-06-13 11:00: Application of the optimal transport Gromov-Wasserstein problem to manifold learning and graph analysis (Hugues Van Assel; École Normale Supérieure de Lyon)

2024-06-13 11:00: Application of the optimal transport Gromov-Wasserstein problem to manifold learning and graph analysis (Hugues Van Assel; École Normale Supérieure de Lyon)

2024-06-13 11:00: Application of the optimal transport Gromov-Wasserstein problem to manifold learning and graph analysis (Hugues Van Assel; École Normale Supérieure de Lyon)