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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)

Auditing Local Explanations is Hard NeurIPS 2024 A Unified Adaptive Testing System Enabled by Hierarchical Structure Search ICML 2024 A Unified and General Framework for Continual Learning ICLR 2024 A Unified Characterization of Private Learnability via Graph Theory COLT 2024 A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits NeurIPS 2024 A Unified Framework for Learning with Nonlinear Model Classes from Arbitrary Linear Samples ICML 2024 A Unified Sampling Framework for Solver Searching of Diffusion Probabilistic Models ICLR 2024 A Unified View of FANOVA: A Comprehensive Bayesian Framework for Component Selection and Estimation ICML 2024 A Unifying Post-Processing Framework for Multi-Objective Learn-to-Defer Problems NeurIPS 2024 A Unifying Variational Framework for Gaussian Process Motion Planning AISTATS 2024 A Universal Class of Sharpness-Aware Minimization Algorithms ICML 2024 A Universal Growth Rate for Learning with Smooth Surrogate Losses NeurIPS 2024 AutoAugment Is What You Need: Enhancing Rule-based Augmentation Methods in Low-resource Regimes EACL 2024 Autobidders with Budget and ROI Constraints: Efficiency, Regret, and Pacing Dynamics COLT 2024 Auto-BPA: An Enhanced Ball-Pivoting Algorithm With Adaptive Radius Using Contextual Bandits WACV 2024 AutoDrop: Training Deep Learning Models with Automatic Learning Rate Drop UAI 2024 Auto-Evolve: Enhancing Large Language Model’s Performance via Self-Reasoning Framework EMNLP 2024 AutoLoRA: Automatically Tuning Matrix Ranks in Low-Rank Adaptation Based on Meta Learning NAACL 2024 autoMALA: Locally adaptive Metropolis-adjusted Langevin algorithm AISTATS 2024 Automated Design of Affine Maximizer Mechanisms in Dynamic Settings AAAI 2024 Automated Efficient Estimation using Monte Carlo Efficient Influence Functions NeurIPS 2024 Automated Loss function Search for Class-imbalanced Node Classification ICML 2024 Automatically Learning Hybrid Digital Twins of Dynamical Systems NeurIPS 2024 Automatic Core-Guided Reformulation via Constraint Explanation and Condition Learning AAAI 2024 Automatic De-Biased Temporal-Relational Modeling for Stock Investment Recommendation IJCAI 2024