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)

Large-Scale Evolution of Image Classifiers ICML 2017 Large-scale Online Kernel Learning with Random Feature Reparameterization IJCAI 2017 Large-Scale Quadratically Constrained Quadratic Program via Low-Discrepancy Sequences NeurIPS 2017 Latent Feature Lasso ICML 2017 Latent Intention Dialogue Models ICML 2017 Lean Crowdsourcing: Combining Humans and Machines in an Online System CVPR 2017 Learned D-AMP: Principled Neural Network based Compressive Image Recovery NeurIPS 2017 Learned Optimizers that Scale and Generalize ICML 2017 Learning a Ground Truth Ranking Using Noisy Approval Votes IJCAI 2017 Learning Co-Substructures by Kernel Dependence Maximization IJCAI 2017 Learning Deep Latent Gaussian Models with Markov Chain Monte Carlo ICML 2017 Learning Disjunctions of Predicates COLT 2017 Learning Dynamics Across Similar Spatiotemporally-Evolving Physical Systems CoRL 2017 Learning Feasibility Constraints for Multicontact Locomotion of Legged Robots RSS 2017 Learning Feature Engineering for Classification IJCAI 2017 Learning Fine-Grained Expressions to Solve Math Word Problems EMNLP 2017 Learning from Conditional Distributions via Dual Embeddings AISTATS 2017 Learning from Data Heterogeneity: Algorithms and Applications IJCAI 2017 Learning from Networked Examples ALT 2017 Learning Gradient Descent: Better Generalization and Longer Horizons ICML 2017 Learning Graphical Games from Behavioral Data: Sufficient and Necessary Conditions AISTATS 2017 Learning Hedonic Games IJCAI 2017 Learning Identifiable Gaussian Bayesian Networks in Polynomial Time and Sample Complexity NeurIPS 2017 Learning Infinite Layer Networks Without the Kernel Trick ICML 2017 Learning in POMDPs with Monte Carlo Tree Search ICML 2017