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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)

AstroNet: When Astrocyte Meets Artificial Neural Network CVPR 2023 A Survey of Methods for Automated Algorithm Configuration (Extended Abstract) IJCAI 2023 A Survey of MWE Identification Experiments: The Devil is in the Details EACL 2023 A Survey on Dataset Distillation: Approaches, Applications and Future Directions IJCAI 2023 A Survey on Efficient Training of Transformers IJCAI 2023 A Symbolic Approach to Computing Disjunctive Association Rules from Data IJCAI 2023 Asymptotically Optimal Quantile Pure Exploration for Infinite-Armed Bandits NeurIPS 2023 Asymptotic confidence sets for random linear programs COLT 2023 Asymptotic Instance-Optimal Algorithms for Interactive Decision Making ICLR 2023 Asymptotics of Bayesian Uncertainty Estimation in Random Features Regression NeurIPS 2023 Asymptotics of Network Embeddings Learned via Subsampling JMLR 2023 Asynchronous Distributed Bilevel Optimization ICLR 2023 Asynchronous Gradient Play in Zero-Sum Multi-agent Games ICLR 2023 Asynchronous Iterations in Optimization: New Sequence Results and Sharper Algorithmic Guarantees JMLR 2023 A Systematic Study of Knowledge Distillation for Natural Language Generation with Pseudo-Target Training ACL 2023 A Table-to-Text Framework with Heterogeneous Multidominance Attention and Self-Evaluated Multi-Pass Deliberation EMNLP 2023 A Tale of Sampling and Estimation in Discounted Reinforcement Learning AISTATS 2023 A Tale of Two Efficient Value Iteration Algorithms for Solving Linear MDPs with Large Action Space AISTATS 2023 A Tale of Two Latent Flows: Learning Latent Space Normalizing Flow with Short-Run Langevin Flow for Approximate Inference AAAI 2023 A Targeted Accuracy Diagnostic for Variational Approximations AISTATS 2023 Atari-5: Distilling the Arcade Learning Environment down to Five Games ICML 2023 ATHENA: Mathematical Reasoning with Thought Expansion EMNLP 2023 A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes NeurIPS 2023 A Theoretical Analysis of the Learning Dynamics under Class Imbalance ICML 2023 A Theoretical Analysis of the Test Error of Finite-Rank Kernel Ridge Regression NeurIPS 2023