A bagging SVM to learn from positive and unlabeled examples

A consistent dot product embedding for stochastic blockmodel graphs

A convex model for non-negative matrix factorization and dimensionality reduction on physical space

A D.C. Programming Approach to the Sparse Generalized Eigenvalue Problem

A Flexible, Scalable and Efficient Algorithmic Framework for Primal Graphical Lasso

A General Framework of Dual Certificate Analysis for Structured Sparse Recovery Problems

A General Theory of Concave Regularization for High Dimensional Sparse Estimation Problems

A generalized risk-based approach to segmentation based on hidden Markov models

A Geometric Proof of Calibration

A hierarchical Dirichlet process mixture model for haplotype reconstruction from multi-population data

A Kernel Approach to Tractable Bayesian Nonparametrics

A kernel-based framework for learning graded relations from data

A Large-Deviation Analysis of the Maximum-Likelihood Learning of Markov Tree Structures

A Method for Compressing Parameters in Bayesian Models with Application to Logistic Sequence Prediction Models

A more robust boosting algorithm

A Multivariate Regression Approach to Association Analysis of Quantitative Trait Network

A new protein binding pocket similarity measure based on comparison of 3D atom clouds: application to ligand prediction

A non-negative expansion for small Jensen-Shannon Divergences

A Nonconformity Approach to Model Selection for SVMs

A Nonparametric Frequency Domain EM Algorithm for Time Series Classification with Applications to Spike Sorting and Macro-Economics