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Statistical Learning

4076 directly classified papers

Papers per year

Papers

Geometric entropy minimization (GEM) for anomaly detection and localization NIPS 2006
Learning from Multiple Sources NIPS 2006
An Oracle Inequality for Clipped Regularized Risk Minimizers NIPS 2006
On the Relation Between Low Density Separation, Spectral Clustering and Graph Cuts NIPS 2006
PG-means: learning the number of clusters in data NIPS 2006
Stability Properties of Empirical Risk Minimization over Donsker Classes JMLR 2006
Bounds for the Loss in Probability of Correct Classification Under Model Based Approximation JMLR 2006
Streamwise Feature Selection JMLR 2006
Quantile Regression Forests JMLR 2006
Segmental Hidden Markov Models with Random Effects for Waveform Modeling JMLR 2006
Consistency of Multiclass Empirical Risk Minimization Methods Based on Convex Loss JMLR 2006
Lower Bounds and Aggregation in Density Estimation JMLR 2006
Some Theory for Generalized Boosting Algorithms JMLR 2006
PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier NIPS 2006
Action Elimination and Stopping Conditions for the Multi-Armed Bandit and Reinforcement Learning Problems JMLR 2006
A new inlier identification scheme for robust estimation problems RSS 2006
Diffusion Kernels on Statistical Manifolds JMLR 2005
Asymptotic Model Selection for Naive Bayesian Networks JMLR 2005
Analysis of Variance of Cross-Validation Estimators of the Generalization Error JMLR 2005
Estimating Functions for Blind Separation When Sources Have Variance Dependencies JMLR 2005
Learning from Examples as an Inverse Problem JMLR 2005
Estimation of Non-Normalized Statistical Models by Score Matching JMLR 2005
Asymptotics in Empirical Risk Minimization JMLR 2005
Learning Multiple Tasks with Kernel Methods JMLR 2005
Concentration Bounds for Unigram Language Models JMLR 2005