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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)

On Empirical Risk Minimization with Dependent and Heavy-Tailed Data NeurIPS 2021 On Energy-Based Models with Overparametrized Shallow Neural Networks ICML 2021 One-pass Stochastic Gradient Descent in overparametrized two-layer neural networks AISTATS 2021 One-Round Communication Efficient Distributed M-Estimation AISTATS 2021 One-Shot Federated Learning: Theoretical Limits and Algorithms to Achieve Them JMLR 2021 One-shot Graph Neural Architecture Search with Dynamic Search Space AAAI 2021 One-Shot Neural Ensemble Architecture Search by Diversity-Guided Search Space Shrinking CVPR 2021 One-Sketch-for-All: Non-linear Random Features from Compressed Linear Measurements AISTATS 2021 On Estimating Recommendation Evaluation Metrics under Sampling AAAI 2021 On Estimation in Latent Variable Models ICML 2021 On Focal Loss for Class-Posterior Probability Estimation: A Theoretical Perspective CVPR 2021 On Generating Plausible Counterfactual and Semi-Factual Explanations for Deep Learning AAAI 2021 On Hallucination and Predictive Uncertainty in Conditional Language Generation EACL 2021 On InstaHide, Phase Retrieval, and Sparse Matrix Factorization ICLR 2021 On Interaction Between Augmentations and Corruptions in Natural Corruption Robustness NeurIPS 2021 On Large-Cohort Training for Federated Learning NeurIPS 2021 On Learnability via Gradient Method for Two-Layer ReLU Neural Networks in Teacher-Student Setting ICML 2021 On Learning Continuous Pairwise Markov Random Fields AISTATS 2021 On Learning Domain-Invariant Representations for Transfer Learning with Multiple Sources NeurIPS 2021 On learning sparse vectors from mixture of responses NeurIPS 2021 On Learning Text Style Transfer with Direct Rewards NAACL 2021 Online A-Optimal Design and Active Linear Regression ICML 2021 On Linear Identifiability of Learned Representations ICML 2021 On Linear Stability of SGD and Input-Smoothness of Neural Networks NeurIPS 2021 Online Blind Audio Source Separation Using Recursive Expectation-Maximization Interspeech 2021