Stochastic Methods

Stochastic Optimization for Large-scale Optimal Transport NeurIPS 2016 Stochastic Three-Composite Convex Minimization NeurIPS 2016 Stochastic Variance Reduced Optimization for Nonconvex Sparse Learning ICML 2016 Stochastic Variance Reduction Methods for Saddle-Point Problems NeurIPS 2016 Streaming PCA: Matching Matrix Bernstein and Near-Optimal Finite Sample Guarantees for Oja’s Algorithm COLT 2016 Sub-sampled Newton Methods with Non-uniform Sampling NeurIPS 2016 The Power of Optimization from Samples NeurIPS 2016 The SNOW Theorem and Latency-Optimal Read-Only Transactions OSDI 2016 The Sound of APALM Clapping: Faster Nonsmooth Nonconvex Optimization with Stochastic Asynchronous PALM NeurIPS 2016 Time-Varying Gaussian Process Bandit Optimization AISTATS 2016 Towards Unifying Hamiltonian Monte Carlo and Slice Sampling NeurIPS 2016 Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient ICML 2016 Tracking the Best Expert in Non-stationary Stochastic Environments NeurIPS 2016 Training Neural Networks Without Gradients: A Scalable ADMM Approach ICML 2016 Variational Tempering AISTATS 2016 Verification Based Solution for Structured MAB Problems NeurIPS 2016 XFT: Practical Fault Tolerance beyond Crashes OSDI 2016 A Complete Recipe for Stochastic Gradient MCMC NeurIPS 2015 Active Pointillistic Pattern Search AISTATS 2015 Adaptive Stochastic Alternating Direction Method of Multipliers ICML 2015 Adaptive Stochastic Optimization: From Sets to Paths NeurIPS 2015 Adaptive Strategy for Stratified Monte Carlo Sampling JMLR 2015 Adding vs. Averaging in Distributed Primal-Dual Optimization ICML 2015 Addressing Constraint Robustness to Torque Errors in Task-Space Inverse Dynamics RSS 2015 A Lower Bound for the Optimization of Finite Sums ICML 2015