Divergence measures and a general framework for local variational approximation

No abstract is available for this paper.

• Publication year

  2011

• Venue

  Neural Networks

• Publication date

  2011-12-01

• Fields of study

  Mathematics, Computer Science, Medicine

• Identifiers
  DOI 10.1016/j.neunet.2011.06.004PMID 21719252
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• Bayesian Generalized Kernel Models

  2010cited by this paper
• AN ALTERNATIVE VIEW OF VARIATIONAL BAYES AND MINIMUM VARIATIONAL STOCHASTIC COMPLEXITY Kazuho Watanabe

  2010cited by this paper
• Sparse linear models: Variational approximate inference and Bayesian experimental design

  2009cited by this paper
• Fast Gaussian process methods for point process intensity estimation

  2008cited by this paper
• Stochastic complexities of general mixture models in variational Bayesian learning

  2007cited by this paper
• Phase transitions in the estimation of event rate: a path integral analysis

  2007cited by this paper
• An Empirical Bayesian Strategy for Solving the Simultaneous Sparse Approximation Problem

  2007cited by this paper
• Bayesian Inference and Optimal Design in the Sparse Linear Model

  2007influential reference
• Pattern Recognition and Machine Learning

  2006influential reference
• Clustering with Bregman Divergences

  2005cited by this paper
• Bayesian computation for logistic regression

  2005cited by this paper
• UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence

  2003cited by this paper
• Estimating a State-Space Model from Point Process Observations

  2003cited by this paper
• Variational algorithms for approximate Bayesian inference

  2003cited by this paper
• Bayesian Hierarchical Mixtures of Experts

  2002cited by this paper
• Thesis Supervisor Accepted by.......................................................................

  2001cited by this paper
• Sparse Bayesian Learning and the Relevan e Ve tor Ma hine

  2001influential reference
• Variational Gaussian process classifiers

  2000cited by this paper
• Bayesian parameter estimation via variational methods

  2000influential reference
• Methods of information geometry

  2000cited by this paper
• Inferring Parameters and Structure of Latent Variable Models by Variational Bayes

  1999cited by this paper
• An Introduction to Variational Methods for Graphical Models

  1999cited by this paper
• Computing upper and lower bounds on likelihoods in intractable networks

  1996cited by this paper

• Approximate Empirical Bayes Estimation of the Regularization Parameter in ℓ1 Trend Filtering

  2022cites this paper
• A similarity-based Bayesian mixture-of-experts model

  2020cites this paper
• Metric in Parameter Space

  2019cites this paper
• MAP and Partially Bayesian Learning

  2019cites this paper
• Model-Induced Regularization and Sparsity Inducing Mechanism

  2019cites this paper
• Global Solver for Matrix Factorization

  2019cites this paper
• VB Algorithm under No Conjugacy

  2019cites this paper
• Global Solver for Low-Rank Subspace Clustering

  2019cites this paper
• Unified Theory for Latent Variable Models

  2019cites this paper
• Asymptotic VB Theory of Mixture Models

  2019cites this paper
• Bibliography

  2019cites this paper
• Asymptotic Learning Theory

  2019cites this paper
• Variational Bayesian Learning Theory

  2019cites this paper
• James–Stein Estimator

  2019cites this paper
• Global VB Solution of Fully Observed Matrix Factorization

  2019cites this paper
• Asymptotic VB Theory of Reduced Rank Regression

  2019cites this paper
• Efficient Solver for Sparse Additive Matrix Factorization

  2019cites this paper
• Detailed Description of Overlap Method

  2019cites this paper
• Optimality of Bayesian Learning

  2019cites this paper
• Preface

  2019cites this paper
• VB Algorithm for Multilinear Models

  2019cites this paper
• Asymptotic VB Theory of Other Latent Variable Models

  2019cites this paper
• Performance Analysis of VB Matrix Factorization

  2019cites this paper
• Index

  2019cites this paper
• VB Algorithm for Latent Variable Models

  2019cites this paper
• Bayesian Learning

  2019cites this paper
• Empirical Bayes Estimation for L1 Regularization: A Detailed Analysis in the One-Parameter Lasso Model

  2018cites this paper
• Estimating Adaptive Individual Interests and Needs Based on Online Local Variational Inference for a Logistic Regression Mixture Model

  2018cites this paper
• Bayesian sparse solutions to linear inverse problems with non-stationary noise with Student-t priors

  2015cites this paper
• Stable locality sensitive discriminant analysis for image recognition

  2014cites this paper
• An alternative view of variational Bayes and asymptotic approximations of free energy

  2012cites this paper
• Fourth Workshop on Information Theoretic Methods in Science and Engineering

  2011cites this paper
• MINIMUM VARIATIONAL STOCHASTIC COMPLEXITY AND AVERAGE GENERALIZATION ERROR IN LATENT VARIABLE MODELS

  2011cites this paper
• Approximate Bayesian Estimation of Varying Binomial Process

  2011cites this paper
• Variational Bayesian Learning

  2000cites this paper