Statistical Learning

Probabilistic Relational PCA NeurIPS 2009 Sequential effects reflect parallel learning of multiple environmental regularities NeurIPS 2009 Sparsistent Learning of Varying-coefficient Models with Structural Changes NeurIPS 2009 Statistical Analysis of Semi-Supervised Learning: The Limit of Infinite Unlabelled Data NeurIPS 2009 Statistical Consistency of Top-k Ranking NeurIPS 2009 Subgroup Analysis via Recursive Partitioning JMLR 2009 The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs JMLR 2009 Thresholding Procedures for High Dimensional Variable Selection and Statistical Estimation NeurIPS 2009 Time-rescaling methods for the estimation and assessment of non-Poisson neural encoding models NeurIPS 2009 Toward Provably Correct Feature Selection in Arbitrary Domains NeurIPS 2009 Ultrahigh Dimensional Feature Selection: Beyond The Linear Model JMLR 2009 A Bahadur Representation of the Linear Support Vector Machine JMLR 2008 Adaptive Forward-Backward Greedy Algorithm for Sparse Learning with Linear Models NeurIPS 2008 A general framework for investigating how far the decoding process in the brain can be simplified NeurIPS 2008 An Error Bound Based on a Worst Likely Assignment JMLR 2008 A New Algorithm for Estimating the Effective Dimension-Reduction Subspace JMLR 2008 An improved estimator of Variance Explained in the presence of noise NeurIPS 2008 A Tutorial on Conformal Prediction JMLR 2008 Bayesian Network Score Approximation using a Metagraph Kernel NeurIPS 2008 Characteristic Kernels on Groups and Semigroups NeurIPS 2008 Consistency of Random Forests and Other Averaging Classifiers JMLR 2008 Consistency of the Group Lasso and Multiple Kernel Learning JMLR 2008 Covariance Estimation for High Dimensional Data Vectors Using the Sparse Matrix Transform NeurIPS 2008 Efficient Direct Density Ratio Estimation for Non-stationarity Adaptation and Outlier Detection NeurIPS 2008 Empirical performance maximization for linear rank statistics NeurIPS 2008