UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Scaling Factorial Hidden Markov Models: Stochastic Variational Inference without Messages

Ng, YC; Chilinski, P; Silva, R; (2016) Scaling Factorial Hidden Markov Models: Stochastic Variational Inference without Messages. In: Proceedings of the 29th Conference on Neural Information Processing Systems (NIPS 2016). Neural Information Processing Systems Foundation: Barcelona, Spain. Green open access

[img]
Preview
Text
silva_observational-interventional-priors-for-dose-response-learning(VoR).pdf - Published version

Download (2MB) | Preview

Abstract

Factorial Hidden Markov Models (FHMMs) are powerful models for sequential data but they do not scale well with long sequences. We propose a scalable inference and learning algorithm for FHMMs that draws on ideas from the stochastic variational inference, neural network and copula literatures. Unlike existing approaches, the proposed algorithm requires no message passing procedure among latent variables and can be distributed to a network of computers to speed up learning. Our experiments corroborate that the proposed algorithm does not introduce further approximation bias compared to the proven structured mean-field algorithm, and achieves better performance with long sequences and large FHMMs.

Type: Proceedings paper
Title: Scaling Factorial Hidden Markov Models: Stochastic Variational Inference without Messages
Event: 29th Conference on Neural Information Processing Systems (NIPS 2016)
Open access status: An open access version is available from UCL Discovery
Publisher version: http://papers.nips.cc/book/advances-in-neural-info...
Language: English
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
URI: https://discovery.ucl.ac.uk/id/eprint/1529378
Downloads since deposit
12Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item