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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

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52
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828
3,646
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2000
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Papers (including subtopics)

Identifying Statistical Bias in Dataset Replication ICML 2020 Identity Crisis: Memorization and Generalization Under Extreme Overparameterization ICLR 2020 If beam search is the answer, what was the question? EMNLP 2020 If You Build Your Own NER Scorer, Non-replicable Results Will Come EMNLP 2020 Image denoising via K-SVD with primal-dual active set algorithm WACV 2020 Imitation Attacks and Defenses for Black-box Machine Translation Systems EMNLP 2020 IMPACT: Importance Weighted Asynchronous Architectures with Clipped Target Networks ICLR 2020 ImpatientCapsAndRuns: Approximately Optimal Algorithm Configuration from an Infinite Pool NeurIPS 2020 Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy NeurIPS 2020 Implicit Bias of Gradient Descent based Adversarial Training on Separable Data ICLR 2020 Implicit Bias of Gradient Descent for Wide Two-layer Neural Networks Trained with the Logistic Loss COLT 2020 Implicit competitive regularization in GANs ICML 2020 Implicit differentiation of Lasso-type models for hyperparameter optimization ICML 2020 Implicit Generative Modeling for Efficient Exploration ICML 2020 Implicit Geometric Regularization for Learning Shapes ICML 2020 Implicit Learning Dynamics in Stackelberg Games: Equilibria Characterization, Convergence Analysis, and Empirical Study ICML 2020 Implicit Regularization and Convergence for Weight Normalization NeurIPS 2020 Implicit regularization for deep neural networks driven by an Ornstein-Uhlenbeck like process COLT 2020 Implicit Regularization in Deep Learning May Not Be Explainable by Norms NeurIPS 2020 Importance-Aware Semantic Segmentation in Self-Driving with Discrete Wasserstein Training AAAI 2020 Importance Sampling via Local Sensitivity AISTATS 2020 Improper Learning for Non-Stochastic Control COLT 2020 Improved Algorithms for Conservative Exploration in Bandits AAAI 2020 Improved Algorithms for Convex-Concave Minimax Optimization NeurIPS 2020 Improved Algorithms for Online Submodular Maximization via First-order Regret Bounds NeurIPS 2020