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Statistical Learning

4,117 papers

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Papers

Thresholding Procedures for High Dimensional Variable Selection and Statistical Estimation NIPS 2009
A Data-Driven Approach to Modeling Choice NIPS 2009
Data-driven calibration of linear estimators with minimal penalties NIPS 2009
Fast Learning from Non-i.i.d. Observations NIPS 2009
Matrix Completion from Noisy Entries NIPS 2009
Efficient Moments-based Permutation Tests NIPS 2009
Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness NIPS 2009
Statistical Consistency of Top-k Ranking NIPS 2009
Asymptotic Analysis of MAP Estimation via the Replica Method and Compressed Sensing NIPS 2009
A joint maximum-entropy model for binary neural population patterns and continuous signals NIPS 2009
Hierarchical Modeling of Local Image Features through $L_p$-Nested Symmetric Distributions NIPS 2009
Distribution-Calibrated Hierarchical Classification NIPS 2009
A unified framework for high-dimensional analysis of $M$-estimators with decomposable regularizers NIPS 2009
Local Rules for Global MAP: When Do They Work ? NIPS 2009
Time-rescaling methods for the estimation and assessment of non-Poisson neural encoding models NIPS 2009
Human Rademacher Complexity NIPS 2009
Subgroup Analysis via Recursive Partitioning JMLR 2009
Nearest Neighbor Clustering: A Baseline Method for Consistent Clustering with Arbitrary Objective Functions JMLR 2009
Consistency and Localizability JMLR 2009
On Uniform Deviations of General Empirical Risks with Unboundedness, Dependence, and High Dimensionality JMLR 2009
Entropy Inference and the James-Stein Estimator, with Application to Nonlinear Gene Association Networks JMLR 2009
Learning Approximate Sequential Patterns for Classification JMLR 2009
Ultrahigh Dimensional Feature Selection: Beyond The Linear Model JMLR 2009
The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs JMLR 2009
Computing Maximum Likelihood Estimates in Recursive Linear Models with Correlated Errors JMLR 2009