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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)

Towards Neural Scaling Laws for Time Series Foundation Models ICLR 2025 Towards Optimal Branching of Linear and Semidefinite Relaxations for Neural Network Robustness Certification JMLR 2025 Towards Optimal Evaluation Efficiency for Large Language Models EMNLP 2025 Towards Optimal Multi-draft Speculative Decoding ICLR 2025 Towards Precise Scaling Laws for Video Diffusion Transformers CVPR 2025 Towards Privacy-Preserving Split Learning for ControlNet WACV 2025 Towards Projected and Incremental Pseudo-Boolean Model Counting AAAI 2025 Towards Provably Efficient Learning of Imperfect Information Extensive-Form Games with Linear Function Approximation UAI 2025 Towards Reward Fairness in RLHF: From a Resource Allocation Perspective ACL 2025 Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization ICLR 2025 Towards Robust Comparisons of NLP Models: A Case Study COLING 2025 Towards Robust Influence Functions with Flat Validation Minima ICML 2025 Towards Runtime Analysis of Population-Based Co-evolutionary Algorithms on Sparse Binary Zero-Sum Game AAAI 2025 Towards Scalable and Deep Graph Neural Networks via Noise Masking AAAI 2025 Towards Scalable Topological Regularizers ICLR 2025 Towards Self-Supervised Covariance Estimation in Deep Heteroscedastic Regression ICLR 2025 Towards Source-Free Machine Unlearning CVPR 2025 Towards Stable and Storage-efficient Dataset Distillation: Matching Convexified Trajectory CVPR 2025 Towards Statistical Factuality Guarantee for Large Vision-Language Models EMNLP 2025 Towards Sustainable NLP: Insights from Benchmarking Inference Energy in Large Language Models NAACL 2025 Towards the 30 by 30 Kunming-Montreal Global Biodiversity Framework Target: Optimising Graph Connectivity in Constraint-Based Spatial Planning IJCAI 2025 Towards the Law of Capacity Gap in Distilling Language Models ACL 2025 Towards Trustworthy, Efficient, and Scalable Machine Learning AAAI 2025 Towards Unbiased Information Extraction and Adaptation in Cross-Domain Recommendation AAAI 2025 Towards Understanding Catastrophic Forgetting in Two-layer Convolutional Neural Networks ICML 2025