Stat-Ml
Bayesian learning of noisy Markov decision processes
Justice blocks and predictability of US Supreme Court votes
Nonlinear Dynamic Field Embedding: On Hyperspectral Scene Visualization
Predicting human preferences using the block structure of complex social networks
Active Collaborative Filtering
Bayesian inference for logistic models using Polya-Gamma latent variables
mlpy: Machine Learning Python
Causal Discovery of Linear Cyclic Models from Multiple Experimental Data Sets with Overlapping Variables
Proximal Newton-type methods for minimizing composite functions
Dimensionality Reduction by Local Discriminative Gaussians
Reading Dependencies from Polytree-Like Bayesian Networks
Distributed Parameter Estimation via Pseudo-likelihood
Semi-blind Sparse Image Reconstruction with Application to MRFM
Learning Feature Hierarchies with Centered Deep Boltzmann Machines
Making Early Predictions of the Accuracy of Machine Learning Applications
Algorithm Runtime Prediction: Methods & Evaluation
On the Convergence Properties of Optimal AdaBoost
Role-Dynamics: Fast Mining of Large Dynamic Networks
Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches
Nested Dictionary Learning for Hierarchical Organization of Imagery and Text
Neural Networks for Complex Data
Algorithms and Complexity Results for Exact Bayesian Structure Learning
