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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)

Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation AISTATS 2021 Kernel Functional Optimisation NeurIPS 2021 Kernel Interpolation for Scalable Online Gaussian Processes AISTATS 2021 Kernel Operations on the GPU, with Autodiff, without Memory Overflows JMLR 2021 Kernel regression in high dimensions: Refined analysis beyond double descent AISTATS 2021 Kernel Smoothing, Mean Shift, and Their Learning Theory with Directional Data JMLR 2021 Kernel Stein Discrepancy Descent ICML 2021 Kernel Thinning COLT 2021 Keyphrase Generation with Fine-Grained Evaluation-Guided Reinforcement Learning EMNLP 2021 KNAS: Green Neural Architecture Search ICML 2021 K-N-MOMDPs: Towards Interpretable Solutions for Adaptive Management AAAI 2021 Knocking in the Game of Gin Rummy AAAI 2021 Knowledge-Adaptation Priors NeurIPS 2021 Knowledge Distillation as Semiparametric Inference ICLR 2021 Knowledge Evolution in Neural Networks CVPR 2021 Knowledge Graph Representation Learning using Ordinary Differential Equations EMNLP 2021 Knowledge Refactoring for Inductive Program Synthesis AAAI 2021 Know your limits: Uncertainty estimation with ReLU classifiers fails at reliable OOD detection UAI 2021 KPC: Learning-Based Model Predictive Control with Deterministic Guarantees L4DC 2021 K-shot NAS: Learnable Weight-Sharing for NAS with K-shot Supernets ICML 2021 L2ight: Enabling On-Chip Learning for Optical Neural Networks via Efficient in-situ Subspace Optimization NeurIPS 2021 Label Confusion Learning to Enhance Text Classification Models AAAI 2021 Label Disentanglement in Partition-based Extreme Multilabel Classification NeurIPS 2021 Label Distribution Learning Machine ICML 2021 Label-Imbalanced and Group-Sensitive Classification under Overparameterization NeurIPS 2021