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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)

Learning Partitions from Context NeurIPS 2024 Learning Performance-Improving Code Edits ICLR 2024 Learning Planning-based Reasoning by Trajectories Collection and Process Reward Synthesizing EMNLP 2024 Learning Planning Domains from Non-redundant Fully-Observed Traces: Theoretical Foundations and Complexity Analysis AAAI 2024 Learning Polynomial Problems with SL(2, R)-Equivariance ICLR 2024 Learning Pseudo-Contractive Denoisers for Inverse Problems ICML 2024 Learning Quadruped Locomotion Using Differentiable Simulation CoRL 2024 Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds ICML 2024 Learning Reduced Fluid Dynamics AAAI 2024 Learning Representation for Multitask Learning through Self-Supervised Auxiliary Learning ECCV 2024 Learning Reward for Robot Skills Using Large Language Models via Self-Alignment ICML 2024 Learning Sampling Policy to Achieve Fewer Queries for Zeroth-Order Optimization AISTATS 2024 Learning Shadow Variable Representation for Treatment Effect Estimation under Collider Bias ICML 2024 Learning Small Decision Trees for Data of Low Rank-Width AAAI 2024 Learning Social Welfare Functions NeurIPS 2024 Learning Solution-Aware Transformers for Efficiently Solving Quadratic Assignment Problem ICML 2024 Learning Structural Causal Models through Deep Generative Models: Methods, Guarantees, and Challenges IJCAI 2024 Learning sum of diverse features: computational hardness and efficient gradient-based training for ridge combinations COLT 2024 Learning Surrogates for Offline Black-Box Optimization via Gradient Matching ICML 2024 Learning symmetries via weight-sharing with doubly stochastic tensors NeurIPS 2024 Learning the Expected Core of Strictly Convex Stochastic Cooperative Games NeurIPS 2024 Learning the Infinitesimal Generator of Stochastic Diffusion Processes NeurIPS 2024 Learning the Optimal Policy for Balancing Short-Term and Long-Term Rewards NeurIPS 2024 Learning the Pareto Set Under Incomplete Preferences: Pure Exploration in Vector Bandits AISTATS 2024 Learning the Topology and Behavior of Discrete Dynamical Systems AAAI 2024