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Stochastic Methods

2788 directly classified papers

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Papers

Finite-Time Performance of Distributed Two-Time-Scale Stochastic Approximation L4DC 2020
Order-Dependent Event Models for Agent Interactions IJCAI 2020
Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs IJCAI 2020
On the Convergence of Stochastic Gradient Descent with Low-Rank Projections for Convex Low-Rank Matrix Problems COLT 2020
Embedding Conjugate Gradient in Learning Random Walks for Landscape Connectivity Modeling in Conservation IJCAI 2020
Lower Bounds for Parallel and Randomized Convex Optimization JMLR 2020
Weighted Message Passing and Minimum Energy Flow for Heterogeneous Stochastic Block Models with Side Information JMLR 2020
High probability guarantees for stochastic convex optimization COLT 2020
Revisiting Stochastic Extragradient AISTATS 2020
Practical Locally Private Heavy Hitters JMLR 2020
APKeep: Realtime Verification for Real Networks NSDI 2020
Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations COLT 2020
Memoryless Sequences for General Losses JMLR 2020
Distributed Feature Screening via Componentwise Debiasing JMLR 2020
ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization JMLR 2020
Biased Opinion Dynamics: When the Devil is in the Details IJCAI 2020
Hamiltonian Monte Carlo Swindles AISTATS 2020
Generalized Nonbacktracking Bounds on the Influence JMLR 2020
Graph-Dependent Implicit Regularisation for Distributed Stochastic Subgradient Descent JMLR 2020
Ancestral Gumbel-Top-k Sampling for Sampling Without Replacement JMLR 2020
Scalable Approximate MCMC Algorithms for the Horseshoe Prior JMLR 2020
Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients JMLR 2020
Convergence Rates for the Stochastic Gradient Descent Method for Non-Convex Objective Functions JMLR 2020
A Data Efficient and Feasible Level Set Method for Stochastic Convex Optimization with Expectation Constraints JMLR 2020
Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms JMLR 2020