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

14

29

44

31

52

189

195

212

235

352

382

457

787

816

828

1,066

1,391

1,913

3,012

3,646

4,303

4,450

5,357

6,155

5,854

1,521

2000

'5

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Papers (including subtopics)

Learning Acyclic Probabilistic Circuits Using Test Paths JMLR 2009 Learning Approximate Sequential Patterns for Classification JMLR 2009 Learning a Small Mixture of Trees NeurIPS 2009 Learning Halfspaces with Malicious Noise JMLR 2009 Learning in Markov Random Fields using Tempered Transitions NeurIPS 2009 Learning models of object structure NeurIPS 2009 Learning Nondeterministic Classifiers JMLR 2009 Learning Non-Linear Combinations of Kernels NeurIPS 2009 Learning Permutations with Exponential Weights JMLR 2009 Learning to Rank by Optimizing NDCG Measure NeurIPS 2009 Learning with Compressible Priors NeurIPS 2009 Linearly constrained Bayesian matrix factorization for blind source separation NeurIPS 2009 Locality-sensitive binary codes from shift-invariant kernels NeurIPS 2009 Localizing Bugs in Program Executions with Graphical Models NeurIPS 2009 Local Rules for Global MAP: When Do They Work ? NeurIPS 2009 Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness NeurIPS 2009 Manifold Regularization for SIR with Rate Root-n Convergence NeurIPS 2009 Margin-based Ranking and an Equivalence between AdaBoost and RankBoost JMLR 2009 Markov Properties for Linear Causal Models with Correlated Errors JMLR 2009 Matrix Completion from Noisy Entries NeurIPS 2009 Matrix Completion from Power-Law Distributed Samples NeurIPS 2009 Maximin affinity learning of image segmentation NeurIPS 2009 Maximum Entropy Discrimination Markov Networks JMLR 2009 Maximum likelihood trajectories for continuous-time Markov chains NeurIPS 2009 Measuring model complexity with the prior predictive NeurIPS 2009