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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)

Kernel-Based Tests for Likelihood-Free Hypothesis Testing NeurIPS 2023 Kernel Conditional Moment Constraints for Confounding Robust Inference AISTATS 2023 Kernelized Reinforcement Learning with Order Optimal Regret Bounds NeurIPS 2023 Kernel-Matrix Determinant Estimates from stopped Cholesky Decomposition JMLR 2023 Kernel Neural Optimal Transport ICLR 2023 Kernel Quadrature with Randomly Pivoted Cholesky NeurIPS 2023 Kernel QuantTree ICML 2023 Kernel Stein Discrepancy thinning: a theoretical perspective of pathologies and a practical fix with regularization NeurIPS 2023 K-Nearest-Neighbor Local Sampling Based Conditional Independence Testing NeurIPS 2023 Knowledge Acquisition for Human-In-The-Loop Image Captioning AISTATS 2023 Knowledge Distillation ≈ Label Smoothing: Fact or Fallacy? EMNLP 2023 Knowledge Distillation Performs Partial Variance Reduction NeurIPS 2023 Knowledge Graph Embeddings using Neural Ito Process: From Multiple Walks to Stochastic Trajectories ACL 2023 Knowledge Intensive Learning of Cutset Networks UAI 2023 Koala: An Index for Quantifying Overlaps with Pre-training Corpora EMNLP 2023 Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors NeurIPS 2023 Koopman Kernel Regression NeurIPS 2023 KrADagrad: Kronecker approximation-domination gradient preconditioned stochastic optimization UAI 2023 KRLS: Improving End-to-End Response Generation in Task Oriented Dialog with Reinforced Keywords Learning EMNLP 2023 Kronecker-Factored Approximate Curvature for Modern Neural Network Architectures NeurIPS 2023 Kullback-Leibler Maillard Sampling for Multi-armed Bandits with Bounded Rewards NeurIPS 2023 L0Learn: A Scalable Package for Sparse Learning using L0 Regularization JMLR 2023 L2T-DLN: Learning to Teach with Dynamic Loss Network NeurIPS 2023 Label Correction of Crowdsourced Noisy Annotations with an Instance-Dependent Noise Transition Model NeurIPS 2023 Label Distributionally Robust Losses for Multi-class Classification: Consistency, Robustness and Adaptivity ICML 2023