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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)

Provable Detection of Propagating Sampling Bias in Prediction Models AAAI 2023 Provable Dynamic Fusion for Low-Quality Multimodal Data ICML 2023 Provable Guarantees for Neural Networks via Gradient Feature Learning NeurIPS 2023 Provable Guarantees for Nonlinear Feature Learning in Three-Layer Neural Networks NeurIPS 2023 Provable Memorization Capacity of Transformers ICLR 2023 Provable Multi-instance Deep AUC Maximization with Stochastic Pooling ICML 2023 Provable Pathways: Learning Multiple Tasks over Multiple Paths AAAI 2023 Provable Reset-free Reinforcement Learning by No-Regret Reduction ICML 2023 Provable Robustness against Wasserstein Distribution Shifts via Input Randomization ICLR 2023 Provable Sim-to-real Transfer in Continuous Domain with Partial Observations ICLR 2023 Provably and Practically Efficient Neural Contextual Bandits ICML 2023 Provably Auditing Ordinary Least Squares in Low Dimensions ICLR 2023 Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation ICML 2023 Provably Efficient Algorithm for Nonstationary Low-Rank MDPs NeurIPS 2023 Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization AAAI 2023 Provably Efficient Generalized Lagrangian Policy Optimization for Safe Multi-Agent Reinforcement Learning L4DC 2023 Provably Efficient Model-Free Algorithms for Non-stationary CMDPs AISTATS 2023 Provably Efficient Offline Reinforcement Learning in Regular Decision Processes NeurIPS 2023 Provably Efficient Offline Reinforcement Learning with Perturbed Data Sources ICML 2023 Provably Efficient Reinforcement Learning via Surprise Bound AISTATS 2023 Provably Fast Convergence of Independent Natural Policy Gradient for Markov Potential Games NeurIPS 2023 Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation NeurIPS 2023 Provably Robust and Plausible Counterfactual Explanations for Neural Networks via Robust Optimisation ACML 2023 Provably Robust Temporal Difference Learning for Heavy-Tailed Rewards NeurIPS 2023 Provably Safe Reinforcement Learning with Step-wise Violation Constraints NeurIPS 2023