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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 with Logical Constraints but without Shortcut Satisfaction ICLR 2023 Learning with Stochastic Orders ICLR 2023 Learn to Accumulate Evidence from All Training Samples: Theory and Practice ICML 2023 Least Squares Model Averaging for Distributed Data JMLR 2023 LECO: Improving Early Exiting via Learned Exits and Comparison-based Exiting Mechanism ACL 2023 LegendreTron: Uprising Proper Multiclass Loss Learning ICML 2023 Length Does Matter: Summary Length can Bias Summarization Metrics EMNLP 2023 Let’s Sample Step by Step: Adaptive-Consistency for Efficient Reasoning and Coding with LLMs EMNLP 2023 Leveraging Demonstrations to Improve Online Learning: Quality Matters ICML 2023 Leveraging Instance Features for Label Aggregation in Programmatic Weak Supervision AISTATS 2023 Leveraging Inter-Rater Agreement for Classification in the Presence of Noisy Labels CVPR 2023 Leveraging the two-timescale regime to demonstrate convergence of neural networks NeurIPS 2023 Leveraging Unlabeled Data to Track Memorization ICLR 2023 Levin Tree Search with Context Models IJCAI 2023 Lexical Repetitions Lead to Rote Learning: Unveiling the Impact of Lexical Overlap in Train and Test Reference Summaries EMNLP 2023 Lexinvariant Language Models NeurIPS 2023 LibMTL: A Python Library for Deep Multi-Task Learning JMLR 2023 LiDAR-in-the-Loop Hyperparameter Optimization CVPR 2023 Lie Group Forced Variational Integrator Networks for Learning and Control of Robot Systems L4DC 2023 Lie Point Symmetry and Physics-Informed Networks NeurIPS 2023 Lifted Bregman Training of Neural Networks JMLR 2023 Likelihood Adjusted Semidefinite Programs for Clustering Heterogeneous Data ICML 2023 Likelihood Ratio Confidence Sets for Sequential Decision Making NeurIPS 2023 Limitations of Information-Theoretic Generalization Bounds for Gradient Descent Methods in Stochastic Convex Optimization ALT 2023 Limitations on approximation by deep and shallow neural networks JMLR 2023