Stochastic Methods

On Markov chain Monte Carlo methods for tall data JMLR 2017 On Perturbed Proximal Gradient Algorithms JMLR 2017 On Tensor Train Rank Minimization : Statistical Efficiency and Scalable Algorithm NeurIPS 2017 On the Equivalence between Kernel Quadrature Rules and Random Feature Expansions JMLR 2017 Open Problem: Meeting Times for Learning Random Automata COLT 2017 Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks ICML 2017 Optimal Posted-Price Mechanism in Microtask Crowdsourcing IJCAI 2017 Optimal Shrinkage of Singular Values Under Random Data Contamination NeurIPS 2017 Optimistic Planning for the Stochastic Knapsack Problem AISTATS 2017 Order Statistics for Probabilistic Graphical Models IJCAI 2017 Phase Transitions in the Pooled Data Problem NeurIPS 2017 Poisson intensity estimation with reproducing kernels AISTATS 2017 Probabilistic Path Hamiltonian Monte Carlo ICML 2017 Provable Self-Representation Based Outlier Detection in a Union of Subspaces CVPR 2017 Provably Safe Robot Navigation with Obstacle Uncertainty RSS 2017 Recovering PCA and Sparse PCA via Hybrid-(l1,l2) Sparse Sampling of Data Elements JMLR 2017 Recursive Sampling for the Nystrom Method NeurIPS 2017 Relativistic Monte Carlo AISTATS 2017 Removing Phase Transitions from Gibbs Measures AISTATS 2017 Resilient Control and Safety for Multi-Agent Cyber-Physical Systems IJCAI 2017 Rigorous Dynamics and Consistent Estimation in Arbitrarily Conditioned Linear Systems NeurIPS 2017 Robust Advertisement Allocation IJCAI 2017 Robust Guarantees of Stochastic Greedy Algorithms ICML 2017 Robust Quadratic Programming for Price Optimization IJCAI 2017 Safe Adaptive Importance Sampling NeurIPS 2017