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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)

Nearest Neighbor Guidance for Out-of-Distribution Detection ICCV 2023 Nearest Neighbor Machine Translation is Meta-Optimizer on Output Projection Layer EMNLP 2023 Nearest-Neighbor Sampling Based Conditional Independence Testing AAAI 2023 Nearest Neighbour with Bandit Feedback NeurIPS 2023 Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game ICLR 2023 Nearly Minimax Optimal Regret for Learning Linear Mixture Stochastic Shortest Path ICML 2023 Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes ICML 2023 Nearly Optimal Algorithms with Sublinear Computational Complexity for Online Kernel Regression ICML 2023 Nearly Optimal Bounds for Cyclic Forgetting NeurIPS 2023 Nearly Optimal Competitive Ratio for Online Allocation Problems with Two-sided Resource Constraints and Finite Requests ICML 2023 Nearly Optimal Latent State Decoding in Block MDPs AISTATS 2023 Nearly Optimal VC-Dimension and Pseudo-Dimension Bounds for Deep Neural Network Derivatives NeurIPS 2023 Nearly-tight Bounds for Deep Kernel Learning ICML 2023 Near-Minimax-Optimal Risk-Sensitive Reinforcement Learning with CVaR ICML 2023 Near-Optimal k-Clustering in the Sliding Window Model NeurIPS 2023 Near-Optimal $Φ$-Regret Learning in Extensive-Form Games ICML 2023 Near-Optimal Adversarial Reinforcement Learning with Switching Costs ICLR 2023 Near-Optimal Algorithms for Gaussians with Huber Contamination: Mean Estimation and Linear Regression NeurIPS 2023 Near-Optimal Algorithms for Private Online Optimization in the Realizable Regime ICML 2023 Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise NeurIPS 2023 Near-optimal Conservative Exploration in Reinforcement Learning under Episode-wise Constraints ICML 2023 Near-Optimal Cryptographic Hardness of Agnostically Learning Halfspaces and ReLU Regression under Gaussian Marginals ICML 2023 Near-Optimal Deployment Efficiency in Reward-Free Reinforcement Learning with Linear Function Approximation ICLR 2023 Near Optimal Heteroscedastic Regression with Symbiotic Learning COLT 2023 Near-optimal learning with average Hölder smoothness NeurIPS 2023