Stat-Ml
Robust Matrix Decomposition with Outliers
Stochastic blockmodels with growing number of classes
Optimal designs for Lasso and Dantzig selector using Expander Codes
K-Dimensional Coding Schemes in Hilbert Spaces
The multi-armed bandit problem with covariates
Matrix Completion from Noisy Entries
Discrete MDL Predicts in Total Variation
On Maximum a Posteriori Estimation of Hidden Markov Processes
A Large-Deviation Analysis of the Maximum-Likelihood Learning of Markov Tree Structures
Increasing stability and interpretability of gene expression signatures
Nuclear norm penalization and optimal rates for noisy low rank matrix completion
Efficient Bayesian Learning in Social Networks with Gaussian Estimators
Online Multiple Kernel Learning for Structured Prediction
Convex Analysis and Optimization with Submodular Functions: a Tutorial
Concentration inequalities of the cross-validation estimator for Empirical Risk Minimiser
A General Theory of Concave Regularization for High Dimensional Sparse Estimation Problems
A Bernstein-type inequality for stochastic processes of quadratic forms of Gaussian variables
Robust PCA via Outlier Pursuit
Asymptotic Normality of Support Vector Machine Variants and Other Regularized Kernel Methods
Measures of Variability for Bayesian Network Graphical Structures
Maximum Entropy Discrimination Markov Networks
Trek separation for Gaussian graphical models
