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Optimization & Theory

43,292 papers (3 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Optimization (17,731) Learning Theory (6,809) Bayesian Inference (6,267) Theory (5,579) Statistical Learning (4,564) Neural Network Optimization (4,155) Stochastic Processes (2,948) Stochastic Methods (1,283) Loss Functions (1,220) Distributed Learning (1,202) Online Algorithms (1,013) Statistics (822) Generalization (376) Information Theory (370) Sample Complexity (282) Sparse Optimization (241) Game Theory (151) Convex Optimization (132) Optimal Transport (104) Robust Optimization (84) Distributed Optimization (73) Approximation Algorithms (33)

Papers per year

1
52
352
828
3,646
5,854
2000
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Papers (including subtopics)

Stochastic Approximation with Decision-Dependent Distributions: Asymptotic Normality and Optimality JMLR 2024 Stochastic Approximation with Delayed Updates: Finite-Time Rates under Markovian Sampling AISTATS 2024 Stochastic Bandits with ReLU Neural Networks ICML 2024 Stochastic Bayesian Optimization with Unknown Continuous Context Distribution via Kernel Density Estimation AAAI 2024 Stochastic Constrained Contextual Bandits via Lyapunov Optimization Based Estimation to Decision Framework COLT 2024 Stochastic-Constrained Stochastic Optimization with Markovian Data JMLR 2024 Stochastic contextual bandits with graph feedback: from independence number to MAS number NeurIPS 2024 Stochastic Controlled Averaging for Federated Learning with Communication Compression ICLR 2024 Stochastic Extragradient with Random Reshuffling: Improved Convergence for Variational Inequalities AISTATS 2024 Stochastic Fine-Tuning of Language Models Using Masked Gradients EMNLP 2024 Stochastic Frank-Wolfe: Unified Analysis and Zoo of Special Cases AISTATS 2024 Stochastic Gradient Descent for Gaussian Processes Done Right ICLR 2024 Stochastic Gradient Flow Dynamics of Test Risk and its Exact Solution for Weak Features ICML 2024 Stochastic Localization via Iterative Posterior Sampling ICML 2024 Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements AISTATS 2024 Stochastic Modified Equations and Dynamics of Dropout Algorithm ICLR 2024 Stochastic Modified Flows, Mean-Field Limits and Dynamics of Stochastic Gradient Descent JMLR 2024 Stochastic Multi-Armed Bandits with Strongly Reward-Dependent Delays AISTATS 2024 Stochastic Neural Simulator for Generalizing Dynamical Systems across Environments IJCAI 2024 Stochastic Newton Proximal Extragradient Method NeurIPS 2024 Stochastic Optimal Control for Diffusion Bridges in Function Spaces NeurIPS 2024 Stochastic Optimal Control Matching NeurIPS 2024 Stochastic Optimization Algorithms for Instrumental Variable Regression with Streaming Data NeurIPS 2024 Stochastic Optimization Schemes for Performative Prediction with Nonconvex Loss NeurIPS 2024 Stochastic Optimization with Arbitrary Recurrent Data Sampling ICML 2024