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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)

Recursive Reasoning in Minimax Games: A Level k Gradient Play Method NeurIPS 2022 Recursive Reinforcement Learning NeurIPS 2022 Recycling Model Updates in Federated Learning: Are Gradient Subspaces Low-Rank? ICLR 2022 Reducing Flipping Errors in Deep Neural Networks AAAI 2022 Reducing uncertainty at the score-to-LR stage in likelihood ratio-based forensic voice comparison using automatic speaker recognition systems Interspeech 2022 Redundant representations help generalization in wide neural networks NeurIPS 2022 Re-evaluating Word Mover’s Distance ICML 2022 Re-Examining Calibration: The Case of Question Answering EMNLP 2022 Re-Examining System-Level Correlations of Automatic Summarization Evaluation Metrics NAACL 2022 Refined Convergence Rates for Maximum Likelihood Estimation under Finite Mixture Models ICML 2022 Refined Lower Bounds for Nearest Neighbor Condensation ALT 2022 Refining DNN-based Mask Estimation using CGMM-based EM Algorithm for Multi-channel Noise Reduction Interspeech 2022 Reflash Dropout in Image Super-Resolution CVPR 2022 Region-dependent temperature scaling for certainty calibration and application to class-imbalanced token classification ACL 2022 Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization AISTATS 2022 Regret Bounds for Information-Directed Reinforcement Learning NeurIPS 2022 Regret Bounds for Stochastic Shortest Path Problems with Linear Function Approximation ICML 2022 Regret guarantees for model-based reinforcement learning with long-term average constraints UAI 2022 Regret Minimization with Performative Feedback ICML 2022 Regret, stability & fairness in matching markets with bandit learners AISTATS 2022 REGroup: Rank-Aggregating Ensemble of Generative Classifiers for Robust Predictions WACV 2022 Regularization Guarantees Generalization in Bayesian Reinforcement Learning through Algorithmic Stability AAAI 2022 Regularization Penalty Optimization for Addressing Data Quality Variance in OoD Algorithms AAAI 2022 Regularized Gradient Descent Ascent for Two-Player Zero-Sum Markov Games NeurIPS 2022 Regularized Modal Regression on Markov-Dependent Observations: A Theoretical Assessment AAAI 2022