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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)

Data Selection for Fine-tuning Large Language Models Using Transferred Shapley Values ACL 2023 Dataset Condensation With Distribution Matching WACV 2023 Dataset Distillation with Convexified Implicit Gradients ICML 2023 Dataset Pruning: Reducing Training Data by Examining Generalization Influence ICLR 2023 Dataset Quantization ICCV 2023 Datasets and Benchmarks for Nanophotonic Structure and Parametric Design Simulations NeurIPS 2023 Data Similarity is Not Enough to Explain Language Model Performance EMNLP 2023 Data Structures for Density Estimation ICML 2023 Data Valuation Without Training of a Model ICLR 2023 DATT: Deep Adaptive Trajectory Tracking for Quadrotor Control CoRL 2023 D-CIPHER: Discovery of Closed-form Partial Differential Equations NeurIPS 2023 Dealing With Cross-Task Class Discrimination in Online Continual Learning CVPR 2023 Dealing with Unknown Variances in Best-Arm Identification ALT 2023 Debias Coarsely, Sample Conditionally: Statistical Downscaling through Optimal Transport and Probabilistic Diffusion Models NeurIPS 2023 Debiased Fine-Tuning for Vision-Language Models by Prompt Regularization AAAI 2023 Debiasing Conditional Stochastic Optimization NeurIPS 2023 Decentralization and Acceleration Enables Large-Scale Bundle Adjustment RSS 2023 Decentralized Learning: Theoretical Optimality and Practical Improvements JMLR 2023 Decentralized Learning With Multi-Headed Distillation CVPR 2023 Decentralized Matrix Sensing: Statistical Guarantees and Fast Convergence NeurIPS 2023 Decentralized Optimistic Hyperpolicy Mirror Descent: Provably No-Regret Learning in Markov Games ICLR 2023 Decentralized Riemannian Algorithm for Nonconvex Minimax Problems AAAI 2023 Decentralized SGD and Average-direction SAM are Asymptotically Equivalent ICML 2023 Decentralized Stochastic Bilevel Optimization with Improved per-Iteration Complexity ICML 2023 Decentralized Stochastic Multi-Player Multi-Armed Walking Bandits AAAI 2023