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Master Class: Particle Filtering and Smoothing for State-Space Models by Arnaud Doucet

CSML

Wednesday, October 3, 2012 from 1:00 PM to 2:00 PM (BST)

Master Class: Particle Filtering and Smoothing for...

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Event Details

State-space models are a popular class of time series models which are ubiquitous in econometrics, ecology, robotics, signal processing, statistics etc. Beyond finite state-space and linear Gaussian models, approximate inference in state-space models relies either on analytical or numerical approximations of the posterior distributions of interest. Particle methods are a class of sequential Monte Carlo methods which are flexible, easily parallelizable and provide consistent estimates. In this talk, I will review standard and advanced particle filtering and smoothing techniques. I will also discuss theoretical results which shed light on the performance of these approaches.

 

This is the first of three talks. There is no need to sign up for the talks on 4 and 5 October (same time and location). For more information please see: http://www.csml.ucl.ac.uk/events/series/10


Lunch will follow each lecture, in the Roberts Building Foyer (G02)

 

Arnaud will be available for individual of group meetings during the day from Monday 1 to Friday 5 October 2012. Please email Victoria Nicholl v.nicholl@ucl.ac.uk

 
Distinguished Lecture: Maximum Likelihood Particle Parameter Estimation for State-Space Models
Thursday 4 October 2012 
Talk: Roberts G06 Sir Ambrose Fleming LT - 13:00-14:00
Lunch: Roberts Foyer G02 - 14:00-15:00
 
Distinguished Lecture: Bayesian Parameter Inference in State-Space Models using Particle Markov chain Monte Car
Friday 5 October 2012 
Talk: Roberts G06 Sir
Ambrose Fleming LT - 13:00-14:00
Lunch: Roberts Foyer G02 - 14:00-15:00

 

Sponsored by DeepMind Technologies: an ambitious London-based startup building general-pupose learning algorithms, with initial product applications in mobile social gaming.


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When & Where


Roberts G06 Sir Ambrose Fleming LT
Malet Place
UCL
WC1E 6BT London
United Kingdom

Wednesday, October 3, 2012 from 1:00 PM to 2:00 PM (BST)


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CSML

The Centre for Computational Statistics and Machine Learning (CSML) spans three departments at University College London, Computer Science, Statistical Science, and the Gatsby Computational Neuroscience Unit. The Centre will pioneer an emerging field that brings together statistics, the recent extensive advances in theoretically well-founded machine learning, and links with a broad range of application areas drawn from across the college, including neuroscience, astrophysics, biological sciences, complexity science, etc. There is a deliberate intention to maintain and cultivate a plurality of approaches within the centre including Bayesian, frequentist, on-line, statistical, etc.

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