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  Bayesian Inference for Sparse Generalized Linear Models

Seeger, M., Gerwinn, S., & Bethge, M. (2007). Bayesian Inference for Sparse Generalized Linear Models. In N. Kok, J. Koronacki, R. Lopez de Mantaras, S. Matwin, D. Mladenic, & A. Skowron (Eds.), Machine Learning: ECML 2007: 18th European Conference on Machine Learning, Warsaw, Poland, September 17-21, 2007 (pp. 298-309). Berlin, Germany: Springer.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-CBD5-B Version Permalink: https://hdl.handle.net/21.11116/0000-0003-D20F-0
Genre: Conference Paper

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https://link.springer.com/content/pdf/10.1007%2F978-3-540-74958-5_29.pdf (Publisher version)
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 Creators:
Seeger, M1, 2, Author           
Gerwinn, S1, 2, 3, Author           
Bethge, M2, 3, Author           
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              
3Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497805              

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 Abstract: We present a framework for efficient, accurate approximate Bayesian inference in generalized linear models (GLMs), based on the expectation propagation (EP) technique. The parameters can be endowed with a factorizing prior distribution, encoding properties such as sparsity or non-negativity. The central role of posterior log-concavity in Bayesian GLMs is emphasized and related to stability issues in EP. In particular, we use our technique to infer the parameters of a point process model for neuronal spiking data from multiple electrodes, demonstrating significantly superior predictive performance when a sparsity assumption is enforced via a Laplace prior distribution.

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 Dates: 2007-09
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1007/978-3-540-74958-5_29
BibTex Citekey: 4807
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Title: 18th European Conference on Machine Learning (ECML 2007)
Place of Event: Warsaw, Poland
Start-/End Date: 2007-09-17 - 2007-09-21

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Title: Machine Learning: ECML 2007: 18th European Conference on Machine Learning, Warsaw, Poland, September 17-21, 2007
Source Genre: Proceedings
 Creator(s):
Kok, NJ, Editor
Koronacki, J, Editor
Lopez de Mantaras, R, Editor
Matwin, S, Editor
Mladenic, D, Editor
Skowron, A, Editor
Affiliations:
-
Publ. Info: Berlin, Germany : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 298 - 309 Identifier: ISBN: 978-3-540-74957-8

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Title: Lecture Notes in Computer Science
Source Genre: Series
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Pages: - Volume / Issue: 4701 Sequence Number: - Start / End Page: - Identifier: -