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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)

Prediction-Powered E-Values ICML 2025 Prediction Risk and Estimation Risk of the Ridgeless Least Squares Estimator under General Assumptions on Regression Errors ICLR 2025 Predictive Modeling of Human Developers’ Evaluative Judgment of Generated Code as a Decision Process EMNLP 2025 Predictive Uncertainty Quantification for Bird's Eye View Segmentation: A Benchmark and Novel Loss Function ICLR 2025 Preference-CFR: Beyond Nash Equilibrium for Better Game Strategies ICML 2025 Preference Consistency Matters: Enhancing Preference Learning in Language Models with Automated Self-Curation of Training Corpora NAACL 2025 Preference Controllable Reinforcement Learning with Advanced Multi-Objective Optimization ICML 2025 Preference Curriculum: LLMs Should Always Be Pretrained on Their Preferred Data ACL 2025 Preference learning made easy: Everything should be understood through win rate ICML 2025 Preference Optimization for Combinatorial Optimization Problems ICML 2025 Preference-Oriented Supervised Fine-Tuning: Favoring Target Model over Aligned Large Language Models AAAI 2025 Prejudge-Before-Think: Enhancing Large Language Models at Test-Time by Process Prejudge Reasoning EMNLP 2025 PREMAP: A Unifying PREiMage APproximation Framework for Neural Networks JMLR 2025 PreSumm: Predicting Summarization Performance Without Summarizing ACL 2025 Pre-trained Models Perform the Best When Token Distributions Follow Zipf’s Law EMNLP 2025 Pre-training CLIP against Data Poisoning with Optimal Transport-based Matching and Alignment EMNLP 2025 Pre-Training Curriculum for Multi-Token Prediction in Language Models ACL 2025 Pre-training Distillation for Large Language Models: A Design Space Exploration ACL 2025 Preventing Network Bottlenecks: Accelerating Datacenter Services with Hotspot-Aware Placement for Compute and Storage NSDI 2025 Prices, Bids, Values: One ML-Powered Combinatorial Auction to Rule Them All ICML 2025 Primal-Dual Neural Algorithmic Reasoning ICML 2025 Principal-Agent Bandit Games with Self-Interested and Exploratory Learning Agents ICML 2025 Principled Algorithms for Optimizing Generalized Metrics in Binary Classification ICML 2025 Principled Content Selection to Generate Diverse and Personalized Multi-Document Summaries ACL 2025 Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples ICML 2025