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Stochastic Methods

1077 directly classified papers

Papers per year

Papers

Hashing Algorithms for Large-Scale Learning NIPS 2011
Stochastic Methods for -regularized Loss Minimization JMLR 2011
Network Flow Algorithms for Structured Sparsity NIPS 2010
A Markov-Chain Monte Carlo Approach to Simultaneous Localization and Mapping AISTATS 2010
Approximate inference in continuous time Gaussian-Jump processes NIPS 2010
Gaussian sampling by local perturbations NIPS 2010
Improving the Asymptotic Performance of Markov Chain Monte-Carlo by Inserting Vortices NIPS 2010
A rational decision making framework for inhibitory control NIPS 2010
Parallelizable Sampling of Markov Random Fields AISTATS 2010
Elliptical slice sampling AISTATS 2010
Fast and Scalable Local Kernel Machines JMLR 2010
Dual Averaging Methods for Regularized Stochastic Learning and Online Optimization JMLR 2010
HOP-MAP: Efficient Message Passing with High Order Potentials AISTATS 2010
Random Walk Approach to Regret Minimization NIPS 2010
Online Learning for Matrix Factorization and Sparse Coding JMLR 2010
Parallelized Stochastic Gradient Descent NIPS 2010
Nonparametric Density Estimation for Stochastic Optimization with an Observable State Variable NIPS 2010
Learning with Blocks: Composite Likelihood and Contrastive Divergence AISTATS 2010
Exploiting Feature Covariance in High-Dimensional Online Learning AISTATS 2010
Inference and Learning in Networks of Queues AISTATS 2010
Randomized Pruning: Efficiently Calculating Expectations in Large Dynamic Programs NIPS 2009
Online Learning of Assignments NIPS 2009
Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling NIPS 2009
Dual Averaging Method for Regularized Stochastic Learning and Online Optimization NIPS 2009
Learning in Markov Random Fields using Tempered Transitions NIPS 2009