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Stochastic Methods

1,118 papers

Papers per year

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33
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Papers

Learning to Crawl AAAI 2020
Trading-Off Static and Dynamic Regret in Online Least-Squares and Beyond AAAI 2020
A Near-Optimal Change-Detection Based Algorithm for Piecewise-Stationary Combinatorial Semi-Bandits AAAI 2020
Low-Variance Black-Box Gradient Estimates for the Plackett-Luce Distribution AAAI 2020
Streaming Batch Gradient Tracking for Neural Network Training (Student Abstract) AAAI 2020
Dynamic Sampling Strategies for Multi-Task Reading Comprehension ACL 2020
Monte-Carlo Graph Search: the Value of Merging Similar States ACML 2020
On the Convergence of SARAH and Beyond AISTATS 2020
Variance Reduction for Evolution Strategies via Structured Control Variates AISTATS 2020
Ordered SGD: A New Stochastic Optimization Framework for Empirical Risk Minimization AISTATS 2020
A Unified Theory of SGD: Variance Reduction, Sampling, Quantization and Coordinate Descent AISTATS 2020
Practical Nonisotropic Monte Carlo Sampling in High Dimensions via Determinantal Point Processes AISTATS 2020
Fast and Furious Convergence: Stochastic Second Order Methods under Interpolation AISTATS 2020
RATQ: A Universal Fixed-Length Quantizer for Stochastic Optimization AISTATS 2020
Linear Convergence of Adaptive Stochastic Gradient Descent AISTATS 2020
Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory AISTATS 2020
Choosing the Sample with Lowest Loss makes SGD Robust AISTATS 2020
Derivative-Free & Order-Robust Optimisation AISTATS 2020
Finite-Time Error Bounds for Biased Stochastic Approximation with Applications to Q-Learning AISTATS 2020
Automated Augmented Conjugate Inference for Non-conjugate Gaussian Process Models AISTATS 2020
An Empirical Study of Stochastic Gradient Descent with Structured Covariance Noise AISTATS 2020
Explicit Mean-Square Error Bounds for Monte-Carlo and Linear Stochastic Approximation AISTATS 2020
Stochastic Variance-Reduced Algorithms for PCA with Arbitrary Mini-Batch Sizes AISTATS 2020
Budget-Constrained Bandits over General Cost and Reward Distributions AISTATS 2020
Finite-Time Analysis of Decentralized Temporal-Difference Learning with Linear Function Approximation AISTATS 2020