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Stochastic Methods

1077 directly classified papers

Papers per year

Papers

Private Adaptive Gradient Methods for Convex Optimization ICML 2021
Asynchronous Distributed Learning : Adapting to Gradient Delays without Prior Knowledge ICML 2021
Approximating a Distribution Using Weight Queries ICML 2021
Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms NIPS 2021
Stability and Generalization of Stochastic Gradient Methods for Minimax Problems ICML 2021
Selective Sampling for Online Best-arm Identification NIPS 2021
Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies ICML 2021
Adversarial Robustness of Streaming Algorithms through Importance Sampling NIPS 2021
SGLB: Stochastic Gradient Langevin Boosting ICML 2021
Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergence NIPS 2021
Conditional Poisson Stochastic Beams EMNLP 2021
Comparison Lift: Bandit-based Experimentation System for Online Advertising AAAI 2021
Derivative-Free & Order-Robust Optimisation AISTATS 2020
A Unified Framework of Online Learning Algorithms for Training Recurrent Neural Networks JMLR 2020
Convergences of Regularized Algorithms and Stochastic Gradient Methods with Random Projections JMLR 2020
Ordered SGD: A New Stochastic Optimization Framework for Empirical Risk Minimization AISTATS 2020
Low-Variance and Zero-Variance Baselines for Extensive-Form Games ICML 2020
SCAFFOLD: Stochastic Controlled Averaging for Federated Learning ICML 2020
Bandits with Adversarial Scaling ICML 2020
On the consistency of graph-based Bayesian semi-supervised learning and the scalability of sampling algorithms JMLR 2020
Generalized Nonbacktracking Bounds on the Influence JMLR 2020
Memoryless Sequences for General Losses JMLR 2020
Accelerating Stratified Sampling SGD by Reconstructing Strata IJCAI 2020
Dynamic Sampling Strategies for Multi-Task Reading Comprehension ACL 2020
Best Arm Identification in Spectral Bandits IJCAI 2020