Stochastic Methods

Stochastic Spectral Descent for Restricted Boltzmann Machines AISTATS 2015 Stochastic Structured Variational Inference AISTATS 2015 StopWasting My Gradients: Practical SVRG NeurIPS 2015 Submodular Point Processes with Applications to Machine learning AISTATS 2015 Taming the Wild: A Unified Analysis of Hogwild-Style Algorithms NeurIPS 2015 The Fundamental Incompatibility of Scalable Hamiltonian Monte Carlo and Naive Data Subsampling ICML 2015 The Hedge Algorithm on a Continuum ICML 2015 Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization ICML 2015 Accelerated Mini-batch Randomized Block Coordinate Descent Method NeurIPS 2014 Adaptive Monte Carlo via Bandit Allocation ICML 2014 Adaptivity of Averaged Stochastic Gradient Descent to Local Strong Convexity for Logistic Regression JMLR 2014 A Filtering Approach to Stochastic Variational Inference NeurIPS 2014 An Accelerated Proximal Coordinate Gradient Method NeurIPS 2014 A second-order bound with excess losses COLT 2014 Asynchronous Anytime Sequential Monte Carlo NeurIPS 2014 Bayesian Sampling Using Stochastic Gradient Thermostats NeurIPS 2014 Black Box Variational Inference AISTATS 2014 Color Transfer Using Probabilistic Moving Least Squares CVPR 2014 Community Detection via Random and Adaptive Sampling COLT 2014 Delay-Tolerant Algorithms for Asynchronous Distributed Online Learning NeurIPS 2014 Distributed Stochastic Gradient MCMC ICML 2014 Efficient Low-Rank Stochastic Gradient Descent Methods for Solving Semidefinite Programs AISTATS 2014 Fast Sampling-Based Inference in Balanced Neuronal Networks NeurIPS 2014 Follow the Leader If You Can, Hedge If You Must JMLR 2014 From Stochastic Mixability to Fast Rates NeurIPS 2014