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Machine Learning

121,146 papers (10 classified directly here)

Subtopics

Learning Types (52,936) Core Methods (48,729) Optimization & Theory (36,874) Application Areas (31,658) Bayesian & Probabilistic (3,963) Learning Paradigms (2,054)

Papers per year

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Papers (including subtopics)

Sparse Semi-supervised Learning Using Conjugate Functions JMLR 2010
Rademacher Complexities and Bounding the Excess Risk in Active Learning JMLR 2010
Hubs in Space: Popular Nearest Neighbors in High-Dimensional Data JMLR 2010
Dual Averaging Methods for Regularized Stochastic Learning and Online Optimization JMLR 2010
Stochastic Composite Likelihood JMLR 2010
Learnability, Stability and Uniform Convergence JMLR 2010
Topology Selection in Graphical Models of Autoregressive Processes JMLR 2010
Using Contextual Representations to Efficiently Learn Context-Free Languages JMLR 2010
Mean Field Variational Approximation for Continuous-Time Bayesian Networks JMLR 2010
Regret Bounds and Minimax Policies under Partial Monitoring JMLR 2010
Information Theoretic Measures for Clusterings Comparison: Variants, Properties, Normalization and Correction for Chance JMLR 2010
Expectation Truncation and the Benefits of Preselection In Training Generative Models JMLR 2010
Linear Algorithms for Online Multitask Classification JMLR 2010
Tree Decomposition for Large-Scale SVM Problems JMLR 2010
Semi-Supervised Novelty Detection JMLR 2010
Gaussian Processes for Machine Learning (GPML) Toolbox JMLR 2010
Covariance in Unsupervised Learning of Probabilistic Grammars JMLR 2010
Inducing Tree-Substitution Grammars JMLR 2010
A Comparison of Optimization Methods and Software for Large-scale L1-regularized Linear Classification JMLR 2010
Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes JMLR 2010
Classification with Incomplete Data Using Dirichlet Process Priors JMLR 2010
Maximum Likelihood in Cost-Sensitive Learning: Model Specification, Approximations, and Upper Bounds JMLR 2010
Learning Instance-Specific Predictive Models JMLR 2010
Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion JMLR 2010
Incremental Sigmoid Belief Networks for Grammar Learning JMLR 2010