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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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'25

Papers (including subtopics)

Learning Linear Complementarity Systems L4DC 2022 Learning Linear Models Using Distributed Iterative Hessian Sketching L4DC 2022 Learning Long-Term Reward Redistribution via Randomized Return Decomposition ICLR 2022 Learning Losses for Strategic Classification AAAI 2022 Learning Low Degree Hypergraphs COLT 2022 Learning Markov Games with Adversarial Opponents: Efficient Algorithms and Fundamental Limits ICML 2022 Learning meta-features for AutoML ICLR 2022 Learning Mixed Multinomial Logits with Provable Guarantees NeurIPS 2022 Learning Mixture of Neural Temporal Point Processes for Multi-dimensional Event Sequence Clustering IJCAI 2022 Learning Mixtures of Linear Dynamical Systems ICML 2022 Learning Mixtures of Random Utility Models with Features from Incomplete Preferences IJCAI 2022 Learning Modular Structures That Generalize Out-of-Distribution (Student Abstract) AAAI 2022 Learning Multi-Objective Curricula for Robotic Policy Learning CoRL 2022 Learning Network Architecture for Open-Set Recognition AAAI 2022 Learning Neural Acoustic Fields NeurIPS 2022 Learning Neural Contextual Bandits through Perturbed Rewards ICLR 2022 Learning Neural Set Functions Under the Optimal Subset Oracle NeurIPS 2022 Learning of Global Objective for Network Flow in Multi-Object Tracking CVPR 2022 Learning on Arbitrary Graph Topologies via Predictive Coding NeurIPS 2022 Learning Operators with Coupled Attention JMLR 2022 Learning Optimal Conformal Classifiers ICLR 2022 Learning Optimal Flows for Non-Equilibrium Importance Sampling NeurIPS 2022 Learning Optimal K-Space Acquisition and Reconstruction Using Physics-Informed Neural Networks CVPR 2022 Learning Optimal Summaries of Clinical Time-series with Concept Bottleneck Models MLHC 2022 Learning Pareto-Efficient Decisions with Confidence AISTATS 2022