Skip to content
conftrace_

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
'5
'10
'15
'20
'25

Papers (including subtopics)

Learning to Defer to Multiple Experts: Consistent Surrogate Losses, Confidence Calibration, and Conformal Ensembles AISTATS 2023 Learning to Estimate Shapley Values with Vision Transformers ICLR 2023 Learning To Exploit the Sequence-Specific Prior Knowledge for Image Processing Pipelines Optimization CVPR 2023 Learning to Extrapolate: A Transductive Approach ICLR 2023 Learning to Generalize Provably in Learning to Optimize AISTATS 2023 Learning to Generate Columns with Application to Vertex Coloring ICLR 2023 Learning to Generate Equitable Text in Dialogue from Biased Training Data ACL 2023 Learning to Group Auxiliary Datasets for Molecule NeurIPS 2023 Learning to Incentivize Information Acquisition: Proper Scoring Rules Meet Principal-Agent Model ICML 2023 Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling ICML 2023 Learning-to-Learn to Guide Random Search: Derivative-Free Meta Blackbox Optimization on Manifold L4DC 2023 Learning to Optimize Differentiable Games ICML 2023 Learning to Optimize with Stochastic Dominance Constraints AISTATS 2023 Learning to Search Feasible and Infeasible Regions of Routing Problems with Flexible Neural k-Opt NeurIPS 2023 Learning to Select Pivotal Samples for Meta Re-weighting AAAI 2023 Learning to Suggest Breaks: Sustainable Optimization of Long-Term User Engagement ICML 2023 Learning to Transform for Generalizable Instance-wise Invariance ICCV 2023 Learning Trajectories are Generalization Indicators NeurIPS 2023 Learning Treatment Effects from Observational and Experimental Data AISTATS 2023 Learning Unnormalized Statistical Models via Compositional Optimization ICML 2023 Learning via Wasserstein-Based High Probability Generalisation Bounds NeurIPS 2023 Learning When to Speak: Latency and Quality Trade-offs for Simultaneous Speech-to-Speech Translation with Offline Models Interspeech 2023 Learning While Scheduling in Multi-Server Systems With Unknown Statistics: MaxWeight with Discounted UCB AISTATS 2023 Learning with Auxiliary Activation for Memory-Efficient Training ICLR 2023 Learning with Explanation Constraints NeurIPS 2023