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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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Papers (including subtopics)

Bounds for Linear Multi-Task Learning JMLR 2006 Bounds for the Loss in Probability of Correct Classification Under Model Based Approximation JMLR 2006 Causal inference in sensorimotor integration NeurIPS 2006 Combining causal and similarity-based reasoning NeurIPS 2006 Conditional mean field NeurIPS 2006 Conditional Random Sampling: A Sketch-based Sampling Technique for Sparse Data NeurIPS 2006 Considering Cost Asymmetry in Learning Classifiers JMLR 2006 Consistency and Convergence Rates of One-Class SVMs and Related Algorithms JMLR 2006 Consistency of Multiclass Empirical Risk Minimization Methods Based on Convex Loss JMLR 2006 Convergence of Laplacian Eigenmaps NeurIPS 2006 Convex Repeated Games and Fenchel Duality NeurIPS 2006 Cross-Validation Optimization for Large Scale Hierarchical Classification Kernel Methods NeurIPS 2006 Data Integration for Classification Problems Employing Gaussian Process Priors NeurIPS 2006 Denoising and Dimension Reduction in Feature Space NeurIPS 2006 Dirichlet-Enhanced Spam Filtering based on Biased Samples NeurIPS 2006 Efficient Learning of Label Ranking by Soft Projections onto Polyhedra JMLR 2006 Efficient sparse coding algorithms NeurIPS 2006 Efficient Structure Learning of Markov Networks using L_1-Regularization NeurIPS 2006 Ensemble Pruning Via Semi-definite Programming JMLR 2006 Environment Identification for a Running Robot Using Inertial and Actuator Cues RSS 2006 Estimating the “Wrong” Graphical Model: Benefits in the Computation-Limited Setting JMLR 2006 Estimation of Gradients and Coordinate Covariation in Classification JMLR 2006 Evolutionary Function Approximation for Reinforcement Learning JMLR 2006 Exact 1-Norm Support Vector Machines Via Unconstrained Convex Differentiable Minimization JMLR 2006 Expectation Correction for Smoothed Inference in Switching Linear Dynamical Systems JMLR 2006