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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
352
828
3,646
5,854
2000
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Papers (including subtopics)

Statistical Rates of Convergence for Functional Partially Linear Support Vector Machines for Classification JMLR 2022 Statistical, Robustness, and Computational Guarantees for Sliced Wasserstein Distances NeurIPS 2022 Steerable Partial Differential Operators for Equivariant Neural Networks ICLR 2022 Steering vector correction in MVDR beamformer for speech enhancement Interspeech 2022 STGN: an Implicit Regularization Method for Learning with Noisy Labels in Natural Language Processing EMNLP 2022 Stochastic Adaptive Activation Function NeurIPS 2022 Stochastic Backpropagation: A Memory Efficient Strategy for Training Video Models CVPR 2022 Stochastic Continuous Submodular Maximization: Boosting via Non-oblivious Function ICML 2022 Stochastic DCA with Variance Reduction and Applications in Machine Learning JMLR 2022 Stochastic Deep Networks with Linear Competing Units for Model-Agnostic Meta-Learning ICML 2022 Stochastic Extragradient: General Analysis and Improved Rates AISTATS 2022 Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusions NeurIPS 2022 Stochastic linear optimization never overfits with quadratically-bounded losses on general data COLT 2022 Stochastic Multiple Target Sampling Gradient Descent NeurIPS 2022 Stochastic Online Learning with Feedback Graphs: Finite-Time and Asymptotic Optimality NeurIPS 2022 Stochastic Reweighted Gradient Descent ICML 2022 Stochastic Rising Bandits ICML 2022 Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Functions NeurIPS 2022 Stochastic smoothing of the top-K calibrated hinge loss for deep imbalanced classification ICML 2022 Stochastic subgradient for composite convex optimization with functional constraints JMLR 2022 Stochastic Training is Not Necessary for Generalization ICLR 2022 Stochastic Trajectory Prediction via Motion Indeterminacy Diffusion CVPR 2022 Stochastic Variance Reduced Ensemble Adversarial Attack for Boosting the Adversarial Transferability CVPR 2022 Stochastic Variance Reduction for Variational Inequality Methods COLT 2022 Stochastic Zeroth-Order Optimization under Nonstationarity and Nonconvexity JMLR 2022