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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
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'25

Papers (including subtopics)

Using Confidence Bounds for Exploitation-Exploration Trade-offs JMLR 2002 Variational Learning of Clusters of Undercomplete Nonsymmetric Independent Components JMLR 2002 A New Approximate Maximal Margin Classification Algorithm JMLR 2001 Bayes Point Machines JMLR 2001 Classes of Kernels for Machine Learning: A Statistics Perspective JMLR 2001 Efficient SVM Training Using Low-Rank Kernel Representations JMLR 2001 Exact Simplification of Support Vector Solutions JMLR 2001 Lagrangian Support Vector Machines JMLR 2001 On the Algorithmic Implementation of Multiclass Kernel-based Vector Machines JMLR 2001 On the Influence of the Kernel on the Consistency of Support Vector Machines JMLR 2001 On the Size of Convex Hulls of Small Sets JMLR 2001 Prior Knowledge and Preferential Structures in Gradient Descent Learning Algorithms JMLR 2001 Sparse Bayesian Learning and the Relevance Vector Machine JMLR 2001 SVMTorch: Support Vector Machines for Large-Scale Regression Problems JMLR 2001 Tracking the Best Linear Predictor JMLR 2001 Uniform Object Generation for Optimizing One-class Classifiers JMLR 2001 Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers JMLR 2000