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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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'25

Papers (including subtopics)

The Role of Outgoing Connection Heterogeneity in Feedforward Layers of Large Language Models EMNLP 2025 The Role of Randomness in Stability ICML 2025 The Sample Complexity of Online Strategic Decision Making with Information Asymmetry and Knowledge Transportability ICML 2025 The Sample Complexity of Stackelberg Games AISTATS 2025 These Aren’t the Vectors You’re Looking For: A Proof of Quantum Advantage in Compositional Generalization AACL 2025 The Sharpness Disparity Principle in Transformers for Accelerating Language Model Pre-Training ICML 2025 Thesis Proposal: Uncertainty in Knowledge Graph Embeddings NAACL 2025 The Size of Teachers as a Measure of Data Complexity: PAC-Bayes Excess Risk Bounds and Scaling Laws AISTATS 2025 The Space Complexity of Learning-Unlearning Algorithms (extended abstract) COLT 2025 The Sparse-Plus-Low-Rank Quasi-Newton Method for Entropic-Regularized Optimal Transport ICML 2025 The Superposition of Diffusion Models Using the Itô Density Estimator ICLR 2025 The Surprising Agreement Between Convex Optimization Theory and Learning-Rate Scheduling for Large Model Training ICML 2025 The Surprising Effectiveness of Infinite-Width NTKs for Characterizing and Improving Model Training AAAI 2025 The Surprising Effectiveness of Test-Time Training for Few-Shot Learning ICML 2025 The Tug of War Within: Mitigating the Fairness-Privacy Conflicts in Large Language Models ACL 2025 The Uniformly Rotated Mondrian Kernel AISTATS 2025 The Utility and Complexity of In- and Out-of-Distribution Machine Unlearning ICLR 2025 The Value of Recall in Extensive-Form Games AAAI 2025 Things Machine Learning Models Know That They Don’t Know AAAI 2025 ThinkAnswer Loss: Balancing Semantic Similarity and Exact Matching for LLM Reasoning Enhancement EMNLP 2025 Think&Cite: Improving Attributed Text Generation with Self-Guided Tree Search and Progress Reward Modeling ACL 2025 Think Clearly: Improving Reasoning via Redundant Token Pruning EMNLP 2025 Thinking Before You Speak: A Proactive Test-time Scaling Approach EMNLP 2025 Thinking LLMs: General Instruction Following with Thought Generation ICML 2025 Thinking Out Loud: Do Reasoning Models Know When They’re Right? EMNLP 2025