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)

MLPs (Mono-Layer Polynomials and Multi-Layer Perceptrons) for Nonlinear Modeling JMLR 2003 On Inclusion-Driven Learning of Bayesian Networks JMLR 2003 On the Performance of Kernel Classes JMLR 2003 On the Proper Learning of Axis-Parallel Concepts JMLR 2003 On the Rate of Convergence of Regularized Boosting Classifiers JMLR 2003 Optimality of Universal Bayesian Sequence Prediction for General Loss and Alphabet JMLR 2003 Optimally-Smooth Adaptive Boosting and Application to Agnostic Learning JMLR 2003 Overfitting in Making Comparisons Between Variable Selection Methods JMLR 2003 Overlearning in Marginal Distribution-Based ICA: Analysis and Solutions JMLR 2003 Ranking a Random Feature for Variable and Feature Selection JMLR 2003 Relational Learning as Search in a Critical Region JMLR 2003 Smooth Boosting and Learning with Malicious Noise JMLR 2003 Sparseness of Support Vector Machines JMLR 2003 Speedup Learning for Repair-based Search by Identifying Redundant Steps JMLR 2003 Statistical Dynamics of On-line Independent Component Analysis JMLR 2003 The em Algorithm for Kernel Matrix Completion with Auxiliary Data JMLR 2003 The Principled Design of Large-Scale Recursive Neural Network Architectures--DAG-RNNs and the Protein Structure Prediction Problem JMLR 2003 Tracking Linear-threshold Concepts with Winnow JMLR 2003 Tree Induction vs. Logistic Regression: A Learning-Curve Analysis JMLR 2003 Tree-Structured Neural Decoding JMLR 2003 Ultraconservative Online Algorithms for Multiclass Problems JMLR 2003 Use of the Zero-Norm with Linear Models and Kernel Methods JMLR 2003 Variable Selection Using SVM-based Criteria JMLR 2003 Algorithmic Luckiness JMLR 2002 A Robust Minimax Approach to Classification JMLR 2002