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Thursday 24 May 2012, 14:00-15:30
Poisson Processes: Applications in Machine Learning
- 👤 Speaker: Amar Shah (University of Cambridge)
- 📅 Date & Time: Thursday 24 May 2012, 14:00 - 15:30
- 📍 Venue: Engineering Department, CBL Room 438
Abstract
Poisson processes form an incredibly powerful class of distributions with elegant modelling properties. Whilst thoroughly studied in the applied probability community over the last few decades, they have yet to stir up a big fuss in the machine learning community. Nonetheless, there have been a collection of fairly recent papers which apply them in a variety of interesting ways.
In this talk I aim to outline some basic definitions and properties of Poisson processes and give a flavour of how they can be used, incorporating some Bayesian nonparametric machinery. To benefit most from the talk, it’d be helpful to familiarise yourself with the definition and basic properties of a Poisson process.
Series This talk is part of the Machine Learning Reading Group @ CUED series.
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