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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

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52
352
828
3,646
5,854
2000
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Papers (including subtopics)

Weak to Strong Learning from Aggregate Labels UAI 2025 Weak-to-Strong Preference Optimization: Stealing Reward from Weak Aligned Model ICLR 2025 Weather Foundation Model Enhanced Decentralized Photovoltaic Power Forecasting Through Spatio-temporal Knowledge Distillation IJCAI 2025 Weight-Aware Activation Sparsity with Constrained Bayesian Optimization Scheduling for Large Language Models EMNLP 2025 Weight-based Analysis of Detokenization in Language Models: Understanding the First Stage of Inference Without Inference NAACL 2025 Weighted Embeddings for Low-Dimensional Graph Representation AAAI 2025 Weighted Euclidean Distance Matrices over Mixed Continuous and Categorical Inputs for Gaussian Process Models AISTATS 2025 Weighted-Reward Preference Optimization for Implicit Model Fusion ICLR 2025 Weights-Rotated Preference Optimization for Large Language Models EMNLP 2025 West Germanic noun-noun compounds and the morphology-syntax trade-off NAACL 2025 WHALE-FL: Wireless and Heterogeneity Aware Latency Efficient Federated Learning over Mobile Devices via Adaptive Subnetwork Scheduling AAAI 2025 What am I missing here?: Evaluating Large Language Models for Masked Sentence Prediction IJCNLP 2025 What Are Step-Level Reward Models Rewarding? Counterintuitive Findings from MCTS-Boosted Mathematical Reasoning AAAI 2025 What Did I Do Wrong? Quantifying LLMs’ Sensitivity and Consistency to Prompt Engineering NAACL 2025 What Does It Mean to Be a Transformer? Insights from a Theoretical Hessian Analysis ICLR 2025 What Do Learning Dynamics Reveal About Generalization in LLM Mathematical Reasoning? ICML 2025 What Do Machine Learning Researchers Mean by “Reproducible”? AAAI 2025 What Goes Into a LM Acceptability Judgment? Rethinking the Impact of Frequency and Length NAACL 2025 What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective ACL 2025 What is the Right Notion of Distance between Predict-then-Optimize Tasks? UAI 2025 What is Wrong with Perplexity for Long-context Language Modeling? ICLR 2025 What Makes for Good Image Captions? EMNLP 2025 What Makes Freezing Layers in Deep Neural Networks Effective? A Linear Separability Perspective AutoML 2025 What Makes In-context Learning Effective for Mathematical Reasoning ICML 2025 What Makes Treatment Effects Identifiable? Characterizations and Estimators Beyond Unconfoundedness (Extended Abstract) COLT 2025