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    JMLR
    2006
    105views more  JMLR 2006»
    Expectation Correction for Smoothed Inference in Switching Linear Dynamical Systems
    13 years 7 months ago
    Expectation Correction for Smoothed Inference in Switching Linear Dynamical Systems
    Download  jmlr.csail.mit.edu
    We introduce a method for approximate smoothed inference in a class of switching linear dynamical systems, based on a novel form of Gaussian Sum smoother. This class includes the ...
    David Barber
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    NIPS
    2007
    190views Information Technology» more  NIPS 2007»
    Bayesian Inference for Spiking Neuron Models with a Sparsity Prior
    13 years 9 months ago
    Bayesian Inference for Spiking Neuron Models with a Sparsity Prior
    Download  books.nips.cc
    Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
    Sebastian Gerwinn, Jakob Macke, Matthias Seeger, M...
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    ECML
    2007
    Springer
    226views Machine Learning» more  ECML 2007»
    Bayesian Inference for Sparse Generalized Linear Models
    14 years 1 months ago
    Bayesian Inference for Sparse Generalized Linear Models
    Download  eprints.pascal-network.org
    We present a framework for efficient, accurate approximate Bayesian inference in generalized linear models (GLMs), based on the expectation propagation (EP) technique. The paramete...
    Matthias Seeger, Sebastian Gerwinn, Matthias Bethg...
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    EMNLP
    2010
    178views Natural Language Processing» more  EMNLP 2010»
    Turbo Parsers: Dependency Parsing by Approximate Variational Inference
    13 years 5 months ago
    Turbo Parsers: Dependency Parsing by Approximate Variational Inference
    Download  www.cs.cmu.edu
    We present a unified view of two state-of-theart non-projective dependency parsers, both approximate: the loopy belief propagation parser of Smith and Eisner (2008) and the relaxe...
    André F. T. Martins, Noah A. Smith, Eric P....
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    CVPR
    2005
    IEEE
    244views Computer Vision» more  CVPR 2005»
    Fields of Experts: A Framework for Learning Image Priors
    14 years 9 months ago
    Fields of Experts: A Framework for Learning Image Priors
    Download  www.cs.brown.edu
    We develop a framework for learning generic, expressive image priors that capture the statistics of natural scenes and can be used for a variety of machine vision tasks. The appro...
    Stefan Roth, Michael J. Black
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