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

Memory-Efficient Gradient Unrolling for Large-Scale Bi-level Optimization NIPS 2024

Stochastic-Constrained Stochastic Optimization with Markovian Data JMLR 2024

Decentralized Multi-Level Compositional Optimization Algorithms with Level-Independent Convergence Rate AISTATS 2024

Stochastic Extragradient with Random Reshuffling: Improved Convergence for Variational Inequalities AISTATS 2024

Understanding Progressive Training Through the Framework of Randomized Coordinate Descent AISTATS 2024

Tuning-Free Maximum Likelihood Training of Latent Variable Models via Coin Betting AISTATS 2024

Breaking the Heavy-Tailed Noise Barrier in Stochastic Optimization Problems AISTATS 2024

A Lower Bound and a Near-Optimal Algorithm for Bilevel Empirical Risk Minimization AISTATS 2024

Accelerating Distributed Stochastic Optimization via Self-Repellent Random Walks ICLR 2024

Sample Efficient Learning of Factored Embeddings of Tensor Fields AISTATS 2024

Complexity of Single Loop Algorithms for Nonlinear Programming with Stochastic Objective and Constraints AISTATS 2024

Trust Region Methods for Nonconvex Stochastic Optimization beyond Lipschitz Smoothness AAAI 2024

SDEs for Minimax Optimization AISTATS 2024

S-SOS: Stochastic Sum-Of-Squares for Parametric Polynomial Optimization NIPS 2024

Improved Evolutionary Algorithms for Submodular Maximization with Cost Constraints IJCAI 2024

Uncertainty informed optimal resource allocation with Gaussian process based Bayesian inference L4DC 2024

Federated X-armed Bandit AAAI 2024

High Probability and Risk-Averse Guarantees for a Stochastic Accelerated Primal-Dual Method JMLR 2024

A Framework for Improving the Reliability of Black-box Variational Inference JMLR 2024

Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits NIPS 2024

Effectiveness of Constant Stepsize in Markovian LSA and Statistical Inference AAAI 2024

Topological Generalization Bounds for Discrete-Time Stochastic Optimization Algorithms NIPS 2024

Sharpened Lazy Incremental Quasi-Newton Method AISTATS 2024

Large-Scale Non-convex Stochastic Constrained Distributionally Robust Optimization AAAI 2024

Stochastic Regularized Majorization-Minimization with weakly convex and multi-convex surrogates JMLR 2024