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stochastic optimization

1060 papers

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Also known as

SO SVRG SSO SGD

Co-occurring keywords

regret bound (1918) online learning (1770) variance reduction (520) multi-armed bandit (1091) convex optimization (1320) convergence rate (606) non-convex optimization (546) stochastic gradient descent (1088) gradient descent (1143) nonconvex optimization (316)

Papers

Scaling-Up Robust Gradient Descent Techniques AAAI 2021
Learning from History for Byzantine Robust Optimization ICML 2021
Learning Complexity of Simulated Annealing AISTATS 2021
A Hybrid Variance-Reduced Method for Decentralized Stochastic Non-Convex Optimization ICML 2021
Fast Learning for Renewal Optimization in Online Task Scheduling JMLR 2021
No-regret Algorithms for Capturing Events in Poisson Point Processes ICML 2021
Distributionally Robust Optimization with Markovian Data ICML 2021
Stochastic Multi-Armed Bandits with Unrestricted Delay Distributions ICML 2021
Sifting through the noise: Universal first-order methods for stochastic variational inequalities NIPS 2021
On the Convergence of SARAH and Beyond AISTATS 2020
Stochastic Loss Function AAAI 2020
An Accelerated DFO Algorithm for Finite-sum Convex Functions ICML 2020
AdaGrad stepsizes: Sharp convergence over nonconvex landscapes JMLR 2020
Stochastic Conditional Gradient Methods: From Convex Minimization to Submodular Maximization JMLR 2020
OSOM: A simultaneously optimal algorithm for multi-armed and linear contextual bandits AISTATS 2020
On Stationary-Point Hitting Time and Ergodicity of Stochastic Gradient Langevin Dynamics JMLR 2020
One Sample Stochastic Frank-Wolfe AISTATS 2020
Communication-Efficient Asynchronous Stochastic Frank-Wolfe over Nuclear-norm Balls AISTATS 2020
On the Complexity Analysis of the Primal Solutions for the Accelerated Randomized Dual Coordinate Ascent JMLR 2020
Improved Sleeping Bandits with Stochastic Action Sets and Adversarial Rewards ICML 2020
Efficient Distributed Hessian Free Algorithm for Large-scale Empirical Risk Minimization via Accumulating Sample Strategy AISTATS 2020
Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization ICML 2020
Stochastic Variance-Reduced Algorithms for PCA with Arbitrary Mini-Batch Sizes AISTATS 2020
Efficient Proximal Mapping of the 1-path-norm of Shallow Networks ICML 2020
Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks ICML 2020