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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)

Nonparametric Identifiability of Causal Representations from Unknown Interventions NeurIPS 2023 Nonparametric Indirect Active Learning AISTATS 2023 Nonparametric Iterative Machine Teaching ICML 2023 Nonparametric Teaching for Multiple Learners NeurIPS 2023 Non-Repeatable Experiments and Non-Reproducible Results: The Reproducibility Crisis in Human Evaluation in NLP ACL 2023 Non-reversible Parallel Tempering for Deep Posterior Approximation AAAI 2023 Non-Smooth Weakly-Convex Finite-sum Coupled Compositional Optimization NeurIPS 2023 Nonstationary Bandit Learning via Predictive Sampling AISTATS 2023 Non-Stationary Bandits with Auto-Regressive Temporal Dependency NeurIPS 2023 Non-stationary Experimental Design under Linear Trends NeurIPS 2023 Non-stationary Online Learning with Memory and Non-stochastic Control JMLR 2023 Non-stationary Reinforcement Learning under General Function Approximation ICML 2023 Non-stationary Risk-Sensitive Reinforcement Learning: Near-Optimal Dynamic Regret, Adaptive Detection, and Separation Design AAAI 2023 Nonstochastic Contextual Combinatorial Bandits AISTATS 2023 No One Idles: Efficient Heterogeneous Federated Learning with Parallel Edge and Server Computation ICML 2023 NoPe-NeRF: Optimising Neural Radiance Field With No Pose Prior CVPR 2023 No-regret Algorithms for Fair Resource Allocation NeurIPS 2023 No-Regret Learning in Two-Echelon Supply Chain with Unknown Demand Distribution AISTATS 2023 No-Regret Learning with Unbounded Losses: The Case of Logarithmic Pooling NeurIPS 2023 No-Regret Linear Bandits beyond Realizability UAI 2023 No-Regret Online Prediction with Strategic Experts NeurIPS 2023 No-Regret Online Reinforcement Learning with Adversarial Losses and Transitions NeurIPS 2023 No-regret Sample-efficient Bayesian Optimization for Finding Nash Equilibria with Unknown Utilities AISTATS 2023 Normalization Layers Are All That Sharpness-Aware Minimization Needs NeurIPS 2023 Normalizing flow neural networks by JKO scheme NeurIPS 2023