stochastic optimization

Stochastic DCA for the Large-sum of Non-convex Functions Problem and its Application to Group Variable Selection in Classification ICML 2017 Stochastic Difference of Convex Algorithm and its Application to Training Deep Boltzmann Machines AISTATS 2017 Stochastic Mirror Descent in Variationally Coherent Optimization Problems NeurIPS 2017 Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite Sum Structure NeurIPS 2017 Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization JMLR 2017 Stochastic Submodular Maximization: The Case of Coverage Functions NeurIPS 2017 Storage Fit Learning with Unlabeled Data IJCAI 2017 SVD-free Convex-Concave Approaches for Nuclear Norm Regularization IJCAI 2017 Task-based End-to-end Model Learning in Stochastic Optimization NeurIPS 2017 Training Deep Networks without Learning Rates Through Coin Betting NeurIPS 2017 Unsupervised Sequential Sensor Acquisition AISTATS 2017 Accelerating Stochastic Composition Optimization NeurIPS 2016 AdaDelay: Delay Adaptive Distributed Stochastic Optimization AISTATS 2016 Adaptive Skills Adaptive Partitions (ASAP) NeurIPS 2016 A Linearly-Convergent Stochastic L-BFGS Algorithm AISTATS 2016 A Self-Correcting Variable-Metric Algorithm for Stochastic Optimization ICML 2016 (Bandit) Convex Optimization with Biased Noisy Gradient Oracles AISTATS 2016 Bridging the Gap between Stochastic Gradient MCMC and Stochastic Optimization AISTATS 2016 Combinatorial Multi-Armed Bandit with General Reward Functions NeurIPS 2016 Combining Adversarial Guarantees and Stochastic Fast Rates in Online Learning NeurIPS 2016 Conservative Bandits ICML 2016 Cyclades: Conflict-free Asynchronous Machine Learning NeurIPS 2016 Efficient Globally Convergent Stochastic Optimization for Canonical Correlation Analysis NeurIPS 2016 Fast Rate Analysis of Some Stochastic Optimization Algorithms ICML 2016 First-order Methods for Geodesically Convex Optimization COLT 2016