Stochastic Methods

Better Mini-Batch Algorithms via Accelerated Gradient Methods NeurIPS 2011 Budgeted Optimization with Concurrent Stochastic-Duration Experiments NeurIPS 2011 Collective Graphical Models NeurIPS 2011 Cross-Entropy Randomized Motion Planning RSS 2011 Distributed Delayed Stochastic Optimization NeurIPS 2011 Efficient Online Learning via Randomized Rounding NeurIPS 2011 Finite Time Analysis of Stratified Sampling for Monte Carlo NeurIPS 2011 Finite-Time Regional Verification of Stochastic Nonlinear Systems RSS 2011 Generative Modeling for Maximizing Precision and Recall in Information Visualization AISTATS 2011 Hashing Algorithms for Large-Scale Learning NeurIPS 2011 Hierarchical Knowledge Gradient for Sequential Sampling JMLR 2011 Improved Algorithms for Linear Stochastic Bandits NeurIPS 2011 Improved Regret Guarantees for Online Smooth Convex Optimization with Bandit Feedback AISTATS 2011 Lightweight Implementations of Probabilistic Programming Languages Via Transformational Compilation AISTATS 2011 Minimax Localization of Structural Information in Large Noisy Matrices NeurIPS 2011 Multi-armed bandits on implicit metric spaces NeurIPS 2011 Neyman-Pearson classification under a strict constraint COLT 2011 Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning NeurIPS 2011 Online Learning: Stochastic, Constrained, and Smoothed Adversaries NeurIPS 2011 Parameter Screening and Optimisation for ILP using Designed Experiments JMLR 2011 Quasi-Newton Methods for Markov Chain Monte Carlo NeurIPS 2011 Randomized Algorithms for Comparison-based Search NeurIPS 2011 Reinforcement Learning using Kernel-Based Stochastic Factorization NeurIPS 2011 Sparse Recovery with Brownian Sensing NeurIPS 2011 Statistical Tests for Optimization Efficiency NeurIPS 2011