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Statistical Learning

4,117 papers

Papers per year

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100
382
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Papers

Localized Sliced Inverse Regression NIPS 2008
Risk Bounds for Randomized Sample Compressed Classifiers NIPS 2008
On the Generalization Ability of Online Strongly Convex Programming Algorithms NIPS 2008
Generalization from Observed to Unobserved Features by Clustering JMLR 2008
A Tutorial on Conformal Prediction JMLR 2008
An Error Bound Based on a Worst Likely Assignment JMLR 2008
Graphical Methods for Efficient Likelihood Inference in Gaussian Covariance Models JMLR 2008
Consistency of the Group Lasso and Multiple Kernel Learning JMLR 2008
A Bahadur Representation of the Linear Support Vector Machine JMLR 2008
A New Algorithm for Estimating the Effective Dimension-Reduction Subspace JMLR 2008
Consistency of Random Forests and Other Averaging Classifiers JMLR 2008
An online Hebbian learning rule that performs Independent Component Analysis NIPS 2007
Catching Up Faster in Bayesian Model Selection and Model Averaging NIPS 2007
Receptive Fields without Spike-Triggering NIPS 2007
Kernel Measures of Conditional Dependence NIPS 2007
Testing for Homogeneity with Kernel Fisher Discriminant Analysis NIPS 2007
Statistical Analysis of Semi-Supervised Regression NIPS 2007
The Distribution Family of Similarity Distances NIPS 2007
A Unified Near-Optimal Estimator For Dimension Reduction in $l_\alpha$ ($0<\alpha\leq 2$) Using Stable Random Projections NIPS 2007
Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization NIPS 2007
Learning with Tree-Averaged Densities and Distributions NIPS 2007
Variational inference for Markov jump processes NIPS 2007
Expectation Maximization and Posterior Constraints NIPS 2007
Optimal ROC Curve for a Combination of Classifiers NIPS 2007
Cluster Stability for Finite Samples NIPS 2007