Skip to content
conftrace_

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
'5
'10
'15
'20
'25

Papers (including subtopics)

A Unified Framework for Generalization Error Analysis of Learning with Arbitrary Discrete Weak Features ICML 2025 A Unified Framework to Enforce, Discover, and Promote Symmetry in Machine Learning JMLR 2025 A Unified Interpretation of Training-Time Out-of-Distribution Detection ICCV 2025 A Unified Loss for Handling Inter-Class and Intra-Class Imbalance in Medical Image Segmentation AAAI 2025 A Unified Model of Direct and Indirect Reciprocity in Multichannel Games AAAI 2025 A Unified Theoretical Analysis of Private and Robust Offline Alignment: from RLHF to DPO ICML 2025 A Unified Theory of Quantum Neural Network Loss Landscapes ICLR 2025 A Unified Theory of Supervised Online Learnability ALT 2025 A Unified View on Learning Unnormalized Distributions via Noise-Contrastive Estimation ICML 2025 A Unifying Information-theoretic Perspective on Evaluating Generative Models AAAI 2025 AutoAL: Automated Active Learning with Differentiable Query Strategy Search ICML 2025 AutoCATE: End-to-End, Automated Treatment Effect Estimation ICML 2025 AutoCCL: Automated Collective Communication Tuning for Accelerating Distributed and Parallel DNN Training NSDI 2025 Autocorrelation Matters: Understanding the Role of Initialization Schemes for State Space Models ICLR 2025 AutoCT: Automating Interpretable Clinical Trial Prediction with LLM Agents EMNLP 2025 AutoDSPy: Automating Modular Prompt Design with Reinforcement Learning for Small and Large Language Models EMNLP 2025 Auto Encoding Neural Process for Multi-interest Recommendation AAAI 2025 AutoEval Done Right: Using Synthetic Data for Model Evaluation ICML 2025 Autoformulation of Mathematical Optimization Models Using LLMs ICML 2025 Automated Fine-Grained Mixture-of-Experts Quantization ACL 2025 Automated Proof of Polynomial Inequalities via Reinforcement Learning CVPR 2025 Automated Superscalar Processor Design by Learning Data Dependencies IJCAI 2025 Automatic debiasing of neural networks via moment-constrained learning CLeaR 2025 Automatic Differentiation of Optimization Algorithms with Time-Varying Updates ICML 2025 Automatic Expert Discovery in LLM Upcycling via Sparse Interpolated Mixture-of-Experts ACL 2025