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Stochastic Methods

1077 directly classified papers

Papers per year

Papers

Path Sample-Analytic Gradient Estimators for Stochastic Binary Networks NIPS 2020
A Catalyst Framework for Minimax Optimization NIPS 2020
Random Reshuffling is Not Always Better NIPS 2020
On the Ergodicity, Bias and Asymptotic Normality of Randomized Midpoint Sampling Method NIPS 2020
The Devil is in the Detail: A Framework for Macroscopic Prediction via Microscopic Models NIPS 2020
Large-Scale Methods for Distributionally Robust Optimization NIPS 2020
Fraunhofer IAIS at FinCausal 2020, Tasks 1 & 2: Using Ensemble Methods and Sequence Tagging to Detect Causality in Financial Documents COLING 2020
Simple and Fast Algorithm for Binary Integer and Online Linear Programming NIPS 2020
On the Convergence of SARAH and Beyond AISTATS 2020
Stochastic Optimization with Laggard Data Pipelines NIPS 2020
Robust, Accurate Stochastic Optimization for Variational Inference NIPS 2020
Temporal Variability in Implicit Online Learning NIPS 2020
Escaping Saddle-Point Faster under Interpolation-like Conditions NIPS 2020
Dynamic Regret of Convex and Smooth Functions NIPS 2020
Least Squares Regression with Markovian Data: Fundamental Limits and Algorithms NIPS 2020
Unbalanced Sobolev Descent NIPS 2020
Low-Variance Black-Box Gradient Estimates for the Plackett-Luce Distribution AAAI 2020
Weighted Sampling for Combined Model Selection and Hyperparameter Tuning AAAI 2020
SVRG for Policy Evaluation with Fewer Gradient Evaluations IJCAI 2020
Uncorrected Least-Squares Temporal Difference with Lambda-Return AAAI 2020
Robust Gradient-Based Markov Subsampling AAAI 2020
An Improved Analysis of Stochastic Gradient Descent with Momentum NIPS 2020
Learning by Repetition: Stochastic Multi-armed Bandits under Priming Effect UAI 2020
Provably Convergent Two-Timescale Off-Policy Actor-Critic with Function Approximation ICML 2020
What You See May Not Be What You Get: UCB Bandit Algorithms Robust to $\varepsilon$-Contamination UAI 2020