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Stochastic Methods

1077 directly classified papers

Papers per year

Papers

Fast Stochastic Variance Reduced ADMM for Stochastic Composition Optimization IJCAI 2017
Nonlinear Acceleration of Stochastic Algorithms NIPS 2017
Expectation Propagation with Stochastic Kinetic Model in Complex Interaction Systems NIPS 2017
Online to Offline Conversions, Universality and Adaptive Minibatch Sizes NIPS 2017
Random Projection Filter Bank for Time Series Data NIPS 2017
A New Alternating Direction Method for Linear Programming NIPS 2017
Asynchronous Stochastic Gradient Descent with Delay Compensation ICML 2017
FALKON: An Optimal Large Scale Kernel Method NIPS 2017
Adaptive SVRG Methods under Error Bound Conditions with Unknown Growth Parameter NIPS 2017
Safe Adaptive Importance Sampling NIPS 2017
Finite Sample Analysis of the GTD Policy Evaluation Algorithms in Markov Setting NIPS 2017
Stochastic Submodular Maximization: The Case of Coverage Functions NIPS 2017
Evaluating the Variance of Likelihood-Ratio Gradient Estimators ICML 2017
Bandit Structured Prediction for Neural Sequence-to-Sequence Learning ACL 2017
Distributed Stochastic Variance Reduced Gradient Methods by Sampling Extra Data with Replacement JMLR 2017
Averaged-DQN: Variance Reduction and Stabilization for Deep Reinforcement Learning ICML 2017
Measuring Sample Quality with Kernels ICML 2017
Less than a Single Pass: Stochastically Controlled Stochastic Gradient AISTATS 2017
Stochastic Modified Equations and Adaptive Stochastic Gradient Algorithms ICML 2017
Improving Gibbs Sampler Scan Quality with DoGS ICML 2017
Fractional Langevin Monte Carlo: Exploring Levy Driven Stochastic Differential Equations for Markov Chain Monte Carlo ICML 2017
Stochastic Gradient Monomial Gamma Sampler ICML 2017
Gradient Boosting on Stochastic Data Streams AISTATS 2017
Rapid Mixing Swendsen-Wang Sampler for Stochastic Partitioned Attractive Models AISTATS 2017
Linear Thompson Sampling Revisited AISTATS 2017