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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)

Mini-batching error and adaptive Langevin dynamics JMLR 2023 Minimalistic Predictions to Schedule Jobs with Online Precedence Constraints ICML 2023 Minimal Width for Universal Property of Deep RNN JMLR 2023 Minimax AUC Fairness: Efficient Algorithm with Provable Convergence AAAI 2023 Minimax-Bayes Reinforcement Learning AISTATS 2023 Minimax Estimation for Personalized Federated Learning: An Alternative between FedAvg and Local Training? JMLR 2023 Minimax estimation of discontinuous optimal transport maps: The semi-discrete case ICML 2023 Minimax Instrumental Variable Regression and L_2 Convergence Guarantees without Identification or Closedness COLT 2023 Minimax Nonparametric Two-Sample Test under Adversarial Losses AISTATS 2023 Minimax Optimal Kernel Operator Learning via Multilevel Training ICLR 2023 Minimax-Optimal Location Estimation NeurIPS 2023 Minimax Optimal Rate for Parameter Estimation in Multivariate Deviated Models NeurIPS 2023 Minimax optimal testing by classification COLT 2023 Minimax Risk Classifiers with 0-1 Loss JMLR 2023 Minimizing Dynamic Regret on Geodesic Metric Spaces COLT 2023 Minimizing Maximum Model Discrepancy for Transferable Black-Box Targeted Attacks CVPR 2023 Minimizing the Accumulated Trajectory Error To Improve Dataset Distillation CVPR 2023 Minimizing Trajectory Curvature of ODE-based Generative Models ICML 2023 Minimum Description Length and Generalization Guarantees for Representation Learning NeurIPS 2023 Minimum-Entropy Coupling Approximation Guarantees Beyond the Majorization Barrier AISTATS 2023 Minimum norm interpolation by perceptra: Explicit regularization and implicit bias NeurIPS 2023 Minimum-Risk Recalibration of Classifiers NeurIPS 2023 Minimum Variance Unbiased N:M Sparsity for the Neural Gradients ICLR 2023 Minimum Width of Leaky-ReLU Neural Networks for Uniform Universal Approximation ICML 2023 Mining Effective Features Using Quantum Entropy for Humor Recognition EACL 2023