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Statistical Learning

4076 directly classified papers

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Papers

Random Design Analysis of Ridge Regression COLT 2012
PAC-Bayesian Bound for Gaussian Process Regression and Multiple Kernel Additive Model COLT 2012
Statistical Optimization in High Dimensions AISTATS 2012
Analysis of a Random Forests Model JMLR 2012
Minimax rates for homology inference AISTATS 2012
Robust Kernel Density Estimation JMLR 2012
PAC-Bayes Bounds with Data Dependent Priors JMLR 2012
Stochastic optimization and sparse statistical recovery: Optimal algorithms for high dimensions NIPS 2012
Competitive Classification and Closeness Testing COLT 2012
Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics JMLR 2012
Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming JMLR 2012
On Ranking and Generalization Bounds JMLR 2012
Consistent Model Selection Criteria on High Dimensions JMLR 2012
Minimax hypothesis testing for curve registration AISTATS 2012
Finite-Sample Analysis of Least-Squares Policy Iteration JMLR 2012
Hyper-Sparse Optimal Aggregation JMLR 2011
Minimum Description Length Penalization for Group and Multi-Task Sparse Learning JMLR 2011
Estimating beta-mixing coefficients AISTATS 2011
Operator Norm Convergence of Spectral Clustering on Level Sets JMLR 2011
Learning Attribute-weighted Voter Model over Social Networks ACML 2011
k-NN Regression Adapts to Local Intrinsic Dimension NIPS 2011
Spectral Dimensionality Reduction via Maximum Entropy AISTATS 2011
Lower Bounds for Passive and Active Learning NIPS 2011
Computationally Efficient Sufficient Dimension Reduction via Squared-Loss Mutual Information ACML 2011
Kernel Regression in the Presence of Correlated Errors JMLR 2011