University of Cambridge > Talks.cam > Machine Learning @ CUED > Non-negative matrix factorization with Gaussian process priors

  Browse A-Z

Log in

Googledetails Microsoftdetails

🔐 Log In

Information on

Subscribing to talksdetails Finding a talkdetails Adding a talkdetails Disseminating talksdetails Help and Documentationdetails

ℹī¸ Information

Non-negative matrix factorization with Gaussian process priors

Download to your calendar using vCal

If you have a question about this talk, please contact Zoubin Ghahramani .

Non-negative matrix factorization (NMF) is a recent method for analyzing matrices of non-negative data. Many physical signals, such as pixel intensities, amplitude spectra, and occurence counts, are naturally represented by non-negative numbers, and in the analysis of mixtures of such data, non-negativity of the individual components is a reasonable constraint. NMF has found widespread use for pattern recognition, clustering, dimensionality reduction in many fields including audio signal processing, image processing, chemometrics and bioinformatics. The first part of this talk gives a general introduction to NMF , with examples from audio signal separation and DNA microarray analysis. The second part of the talk introduces Gaussian process priors in the NMF framework, illustrated with an example from chemical shift brain imaging.

This talk is part of the Machine Learning @ CUED series.

This talk is included in these lists:

Note that ex-directory lists are not shown.

Other lists

SG1/2, Alison Richard Building, Cambridge, CB3 9DT SS02 Hybrid (In-Person + Online). Here is the Google Meet Link: https://meet.google.com/cru-hcuo-rhu David Li Kwok Po Lecture Theatre, Faculty of Law

Other talks

Talk TBC A Novel Diffusion Model based Approach for Sleep Music Generation The search for a new population of strong gravitational lenses with JWST Non-stationarity in structural dynamics, challenges and implications for modelling and structural health monitoring C2D3 Computational Biology Annual Symposium 2026 Welfare Reform and the Imperative of Cooperation
 

Š 2006-2025 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity