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)

Modeling the spacing effect in sequential category learning NeurIPS 2009 Modelling Relational Data using Bayesian Clustered Tensor Factorization NeurIPS 2009 Monte Carlo Sampling for Regret Minimization in Extensive Games NeurIPS 2009 Multi-Label Prediction via Compressed Sensing NeurIPS 2009 Multi-Label Prediction via Sparse Infinite CCA NeurIPS 2009 Multiple Incremental Decremental Learning of Support Vector Machines NeurIPS 2009 Nash Equilibria of Static Prediction Games NeurIPS 2009 Nearest Neighbor Clustering: A Baseline Method for Consistent Clustering with Arbitrary Objective Functions JMLR 2009 Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling NeurIPS 2009 Neurometric function analysis of population codes NeurIPS 2009 Nieme: Large-Scale Energy-Based Models JMLR 2009 Noisy Generalized Binary Search NeurIPS 2009 Nonlinear Models Using Dirichlet Process Mixtures JMLR 2009 Nonparametric Bayesian Models for Unsupervised Event Coreference Resolution NeurIPS 2009 Nonparametric Bayesian Texture Learning and Synthesis NeurIPS 2009 Nonparametric Greedy Algorithms for the Sparse Learning Problem NeurIPS 2009 Nonparametric Latent Feature Models for Link Prediction NeurIPS 2009 Non-stationary continuous dynamic Bayesian networks NeurIPS 2009 On Learning Rotations NeurIPS 2009 Online Learning of Assignments NeurIPS 2009 Online Learning with Sample Path Constraints JMLR 2009 Online Learning with Samples Drawn from Non-identical Distributions JMLR 2009 On Stochastic and Worst-case Models for Investing NeurIPS 2009 On the Algorithmics and Applications of a Mixed-norm based Kernel Learning Formulation NeurIPS 2009 On the Consistency of Feature Selection using Greedy Least Squares Regression JMLR 2009