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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)

Sequential Predictive Two-Sample and Independence Testing NeurIPS 2023 Sequential Subset Matching for Dataset Distillation NeurIPS 2023 Sequential Underspecified Instrument Selection for Cause-Effect Estimation ICML 2023 Seq-UPS: Sequential Uncertainty-Aware Pseudo-Label Selection for Semi-Supervised Text Recognition WACV 2023 SERF: Towards Better Training of Deep Neural Networks Using Log-Softplus ERror Activation Function WACV 2023 Settling the Reward Hypothesis ICML 2023 SGDA with shuffling: faster convergence for nonconvex-PŁ minimax optimization ICLR 2023 SGD learning on neural networks: leap complexity and saddle-to-saddle dynamics COLT 2023 (S)GD over Diagonal Linear Networks: Implicit bias, Large Stepsizes and Edge of Stability NeurIPS 2023 SGD with AdaGrad Stepsizes: Full Adaptivity with High Probability to Unknown Parameters, Unbounded Gradients and Affine Variance ICML 2023 SGD with Large Step Sizes Learns Sparse Features ICML 2023 SGEM: Test-Time Adaptation for Automatic Speech Recognition via Sequential-Level Generalized Entropy Minimization Interspeech 2023 SHAP-IQ: Unified Approximation of any-order Shapley Interactions NeurIPS 2023 Shapley Head Pruning: Identifying and Removing Interference in Multilingual Transformers EACL 2023 Sharing Pattern Submodels for Prediction with Missing Values AAAI 2023 Sharp analysis of EM for learning mixtures of pairwise differences COLT 2023 Sharp Calibrated Gaussian Processes NeurIPS 2023 Sharper Analysis for Minibatch Stochastic Proximal Point Methods: Stability, Smoothness, and Deviation JMLR 2023 Sharper Bounds for ℓ_p Sensitivity Sampling ICML 2023 Sharper Bounds for Uniformly Stable Algorithms with Stationary Mixing Process ICLR 2023 Sharper Model-free Reinforcement Learning for Average-reward Markov Decision Processes COLT 2023 Sharpness-Aware Gradient Matching for Domain Generalization CVPR 2023 Sharpness-Aware Minimization Leads to Low-Rank Features NeurIPS 2023 Sharpness Minimization Algorithms Do Not Only Minimize Sharpness To Achieve Better Generalization NeurIPS 2023 Sharp Spectral Rates for Koopman Operator Learning NeurIPS 2023