Natural Conjugate Gradient in Variational Inference

No abstract is available for this paper.

• Publication year

  2007

• Venue

  International Conference on Neural Information Processing

• Publication date

  Unknown publication date

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.1007/978-3-540-69162-4_32
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Pattern Recognition and Machine Learning

  2006cited by this paper
• A Note on Conjugate Natural Gradient Training of Multilayer Perceptrons

  2006cited by this paper
• Variational Message Passing

  2005cited by this paper
• Unsupervised Variational Bayesian Learning of Nonlinear Models

  2004cited by this paper
• Hierarchical models of variance sources

  2004cited by this paper
• Accelerating Cyclic Update Algorithms for Parameter Estimation by Pattern Searches

  2003cited by this paper
• Adaptive Overrelaxed Bound Optimization Methods

  2003cited by this paper
• Optimization with EM and Expectation-Conjugate-Gradient

  2003cited by this paper
• An Unsupervised Ensemble Learning Method for Nonlinear Dynamic State-Space Models

  2002influential reference
• Online Model Selection Based on the Variational Bayes

  2001cited by this paper
• Information Geometry of Mean-Field Approximation

  2000cited by this paper
• Propagation Algorithms for Variational Bayesian Learning

  2000cited by this paper
• Bayesian Non-Linear Independent Component Analysis by Multi-Layer Perceptrons

  2000cited by this paper
• Advances in Independent Component Analysis

  2000cited by this paper
• Bayesian Ensemble Learning for Nonlinear Factor Analysis

  2000cited by this paper
• Bayesian Model Selection for Support Vector Machines, Gaussian Processes and Other Kernel Classifiers

  1999cited by this paper
• Natural Gradient Works Efficiently in Learning

  1998cited by this paper
• The Geometry of Algorithms with Orthogonality Constraints

  1998cited by this paper
• Ensemble Learning for Multi-Layer Networks

  1997cited by this paper
• Adaptive Online Learning Algorithms for Blind Separation: Maximum Entropy and Minimum Mutual Information

  1997cited by this paper
• The EM algorithm and extensions

  1996cited by this paper
• Information geometry of the EM and em algorithms for neural networks

  1995cited by this paper
• Differential Geometry and Statistics

  1993cited by this paper
• Theory of algorithms for unconstrained optimization

  1992cited by this paper
• Differential-geometrical methods in statistics

  1985cited by this paper

• Natural Gradient VI: Guarantees for Non-Conjugate Models

  2025cites this paper
• Optimization Guarantees for Square-Root Natural-Gradient Variational Inference

  2025influential citation
• Magnetic ground state of supported monatomic Fe chains from first principles

  2022cites this paper
• Efficient Approximate Inference for Stationary Kernel on Frequency Domain

  2022cites this paper
• Variational inference and sparsity in high-dimensional deep Gaussian mixture models

  2021cites this paper
• Bayesian Neural Networks

  2021cites this paper
• Variational posterior approximation using stochastic gradient ascent with adaptive stepsize

  2021cites this paper
• Non-conjugate Posterior using Stochastic Gradient Ascent with Adaptive Stepsize

  2020cites this paper
• Variational Inference of Dirichlet Process Mixture using Stochastic Gradient Ascent

  2020influential citation
• Manifold Optimization-Assisted Gaussian Variational Approximation

  2019cites this paper
• Large-scale variational inference for Bayesian joint regression modelling of high-dimensional genetic data

  2019cites this paper
• Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations

  2019cites this paper
• Natural Gradient Deep Q-learning

  2018cites this paper
• Social Recommendation with Missing Not at Random Data

  2018cites this paper
• Modèles de mélange pour la séparation multicanale de sources sonores en milieu réverbérant

  2017cites this paper
• Advances in Variational Inference

  2017cites this paper
• Semiparametric Mean Field Variational Bayes: General Principles and Numerical Issues

  2016cites this paper
• Variational Inference: A Review for Statisticians

  2016cites this paper
• Distributed Variational Bayesian Algorithms Over Sensor Networks

  2016cites this paper
• Efficient inference for genetic association studies with multiple outcomes

  2016cites this paper
• Correlated Random Measures: Appendix

  2016cites this paper
• Correlated Random Measures

  2015cites this paper
• Scalable Bayesian Induction of Word Embeddings

  2015cites this paper
• On Recurrent and Deep Neural Networks

  2015cites this paper
• Training Conditional Random Fields with Natural Gradient Descent

  2015cites this paper
• Zero-Inflated Poisson Factorization for Recommendation Systems

  2014cites this paper
• A Fast Inference Algorithm for Stochastic Blockmodel

  2014cites this paper
• Comparison-based natural gradient optimization in high dimension

  2014cites this paper
• Automated Variational Inference in Probabilistic Programming

  2013cites this paper
• Revisiting Natural Gradient for Deep Networks

  2013cites this paper
• Scalable Recommendation with Poisson Factorization

  2013cites this paper
• A Stochastic Variational Framework for Fitting and Diagnosing Generalized Linear Mixed Models

  2012influential citation
• Stochastic variational inference

  2012cites this paper
• Face Recognition System using Discrete Cosine Transform combined with MLP and RBF Neural Networks

  2012cites this paper
• Non-conjugate Variational Message Passing for Multinomial and Binary Regression

  2011cites this paper
• Probabilistic prototype models for attributed graphs

  2011cites this paper
• Riemann manifold Langevin and Hamiltonian Monte Carlo methods

  2011cites this paper
• Learning on Relational Data: Prototype-Based Classification of Attributed Graphs

  2011cites this paper
• Natural Policy Gradient Methods with Parameter-based Exploration for Control Tasks

  2010cites this paper
• Bidirectional Relation between CMA Evolution Strategies and Natural Evolution Strategies

  2010cites this paper
• Variational inference and learning for non-linear state-space models with state-dependent observation noise

  2010cites this paper
• Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes

  2010influential citation
• Algorithms for Variational Learning of Mixture of Gaussians

  2009cites this paper
• A gradient-based algorithm competitive with variational Bayesian EM for mixture of Gaussians

  2009cites this paper
• Gaussian-process factor analysis for modeling spatio-temporal data

  2009cites this paper
• Natural Conjugate Gradient on Complex Flag Manifolds for Complex Independent Subspace Analysis

  2008cites this paper
• Variational Inference and Learning for Continuous-Time Nonlinear State-Space Models

  2008cites this paper
• Bayesian learning of latent variable models

  2008cites this paper
• Advanced source separation methods with applications to spatio-temporal datasets

  2006cites this paper
• Bayesian Learning of Latent Variable Models

  year unknowncites this paper
• A variational approach to empirical mode estimation

  year unknowncites this paper