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

Provable convergence guarantees for black-box variational inference NIPS 2023

Nash Regret Guarantees for Linear Bandits NIPS 2023

Optimal Extragradient-Based Algorithms for Stochastic Variational Inequalities with Separable Structure NIPS 2023

Target-based Surrogates for Stochastic Optimization ICML 2023

Mobilizing Personalized Federated Learning in Infrastructure-Less and Heterogeneous Environments via Random Walk Stochastic ADMM NIPS 2023

Fast Rank-1 Lattice Targeted Sampling for Black-box Optimization NIPS 2023

Non-Smooth Weakly-Convex Finite-sum Coupled Compositional Optimization NIPS 2023

First Order Stochastic Optimization with Oblivious Noise NIPS 2023

Randomized Greedy Learning for Non-monotone Stochastic Submodular Maximization Under Full-bandit Feedback AISTATS 2023

ASkewSGD : An Annealed interval-constrained Optimisation method to train Quantized Neural Networks AISTATS 2023

Probably Anytime-Safe Stochastic Combinatorial Semi-Bandits ICML 2023

PROTES: Probabilistic Optimization with Tensor Sampling NIPS 2023

Delayed Algorithms for Distributed Stochastic Weakly Convex Optimization NIPS 2023

Stochastic Approximation Approaches to Group Distributionally Robust Optimization NIPS 2023

A Unified Approach for Maximizing Continuous DR-submodular Functions NIPS 2023

Sample Complexity for Quadratic Bandits: Hessian Dependent Bounds and Optimal Algorithms NIPS 2023

Breaking the Lower Bound with (Little) Structure: Acceleration in Non-Convex Stochastic Optimization with Heavy-Tailed Noise COLT 2023

High Probability Bounds for Stochastic Continuous Submodular Maximization AISTATS 2023

A Fully First-Order Method for Stochastic Bilevel Optimization ICML 2023

Achieving $\mathcal{O}(\epsilon^{-1.5})$ Complexity in Hessian/Jacobian-free Stochastic Bilevel Optimization NIPS 2023

Stochastic Methods for AUC Optimization subject to AUC-based Fairness Constraints AISTATS 2023

Orthogonal Directions Constrained Gradient Method: from non-linear equality constraints to Stiefel manifold COLT 2023

The Acquisition of Physical Knowledge in Generative Neural Networks ICML 2023

Unbiased Compression Saves Communication in Distributed Optimization: When and How Much? NIPS 2023

Buying Information for Stochastic Optimization ICML 2023