stochastic optimization

Budgeted Optimization with Concurrent Stochastic-Duration Experiments NeurIPS 2011 Distributed Delayed Stochastic Optimization NeurIPS 2011 Empirical Risk Minimization of Graphical Model Parameters Given Approximate Inference, Decoding, and Model Structure AISTATS 2011 Improved Regret Guarantees for Online Smooth Convex Optimization with Bandit Feedback AISTATS 2011 Quasi-Newton Methods for Markov Chain Monte Carlo NeurIPS 2011 Sparse Recovery with Brownian Sensing NeurIPS 2011 Sparsity Regret Bounds for Individual Sequences in Online Linear Regression COLT 2011 Statistical Optimization of Non-Negative Matrix Factorization AISTATS 2011 Statistical Tests for Optimization Efficiency NeurIPS 2011 Stochastic convex optimization with bandit feedback NeurIPS 2011 Stochastic Methods for -regularized Loss Minimization JMLR 2011 The KL-UCB Algorithm for Bounded Stochastic Bandits and Beyond COLT 2011 Learning with Blocks: Composite Likelihood and Contrastive Divergence AISTATS 2010 Nonparametric Density Estimation for Stochastic Optimization with an Observable State Variable NeurIPS 2010 Online Learning for Latent Dirichlet Allocation NeurIPS 2010 Online Learning in The Manifold of Low-Rank Matrices NeurIPS 2010 Throttling Poisson Processes NeurIPS 2010 Accelerated Gradient Methods for Stochastic Optimization and Online Learning NeurIPS 2009 A General Projection Property for Distribution Families NeurIPS 2009 Dual Averaging Method for Regularized Stochastic Learning and Online Optimization NeurIPS 2009 Information-theoretic lower bounds on the oracle complexity of convex optimization NeurIPS 2009 Online Learning with Sample Path Constraints JMLR 2009 Periodic Step Size Adaptation for Single Pass On-line Learning NeurIPS 2009 Slow Learners are Fast NeurIPS 2009 Algorithms for Infinitely Many-Armed Bandits NeurIPS 2008