Stat-Ml
Focus of Attention for Linear Predictors
A Plea for Neutral Comparison Studies in Computational Sciences
Small-sample Brain Mapping: Sparse Recovery on Spatially Correlated Designs with Randomization and Clustering
Distributed optimization of deeply nested systems
The Author-Topic Model for Authors and Documents
Learning Bayesian Network Parameters with Prior Knowledge about Context-Specific Qualitative Influences
Spike-and-Slab Sparse Coding for Unsupervised Feature Discovery
Learning to Identify Regular Expressions that Describe Email Campaigns
(weak) Calibration is Computationally Hard
Collaborative Filtering and the Missing at Random Assumption
Co-clustering separately exchangeable network data
Ensemble Methods for Convex Regression with Applications to Geometric Programming Based Circuit Design
A Non-Parametric Bayesian Method for Inferring Hidden Causes
Large Scale Variational Bayesian Inference for Structured Scale Mixture Models
How To Grade a Test Without Knowing the Answers --- A Bayesian Graphical Model for Adaptive Crowdsourcing and Aptitude Testing
Demand-Driven Clustering in Relational Domains for Predicting Adverse Drug Events
Similarity Learning for Provably Accurate Sparse Linear Classification
A Linear Approximation to the chi^2 Kernel with Geometric Convergence
Evaluating Classifiers Without Expert Labels
Semi-blind Source Separation via Sparse Representations and Online Dictionary Learning
Topic Extraction and Bundling of Related Scientific Articles
Learning a peptide-protein binding affinity predictor with kernel ridge regression
