Bayesian Inference for Big Data with Stochastic Gradient Markov Chain Monte Carlo

Lead Research Organisation: University of Oxford
Department Name: Statistics

Abstract

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Publications

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A Bouchard-Côté (2015) The Bouncy Particle Sampler: A Non-Reversible Rejection-Free Markov Chain Monte Carlo Method

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Teh, YW (2015) Distributed Bayesian Learning with Stochastic Natural-gradient Expectation Propagation and the Posterior Server

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Döbler, C (2015) An iterative technique for bounding derivatives of solutions of Stein equations

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Del Moral P (2015) Uniform Stability of a Particle Approximation of the Optimal Filter Derivative in SIAM Journal on Control and Optimization

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Bouchard-Côté A (2018) The Bouncy Particle Sampler: A Nonreversible Rejection-Free Markov Chain Monte Carlo Method in Journal of the American Statistical Association

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Bardenet R On Markov chain Monte Carlo Methods for Tall Data in Journal of Machine Learning Research

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Bardenet Remi (2017) On Markov chain Monte Carlo methods for tall data in JOURNAL OF MACHINE LEARNING RESEARCH

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Yildirim S (2013) An Online Expectation-Maximization Algorithm for Changepoint Models in Journal of Computational and Graphical Statistics

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Bishop A (2014) Distributed Nonlinear Consensus in the Space of Probability Measures in IFAC Proceedings Volumes

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Hasenclever Leonard (2015) Distributed Bayesian Learning with Stochastic Natural-gradient Expectation Propagation and the Posterior Server in arXiv e-prints

 
Description We are studying sophisticated new statistical methods to analyze big data sets. Current methods are very computationally intensive and do not scale in presence of big data. We are developing scalable yet sophisticated techniques to extract useful information from massive datasets.
Exploitation Route There is still a lot of room for improvement, both methodologically and theoretically. So we expect over the forthcoming year to develop further our new algorithms.
Sectors Aerospace, Defence and Marine,Digital/Communication/Information Technologies (including Software),Electronics,Security and Diplomacy
URL http://www.stats.ox.ac.uk/~doucet/journalsbysubject.html