Gaussian Mixture Modeling with Gaussian Process Latent Variable Models

Gaussian Process Regression Networks

Gaussian Process Regression with a Student-t Likelihood

Generalization error bounds for stationary autoregressive models

Geometry of the restricted Boltzmann machine

Gradient-based kernel dimension reduction for supervised learning

Graph Construction for Learning with Unbalanced Data

Graph-Structured Multi-task Regression and an Efficient Optimization Method for General Fused Lasso

Graph-Valued Regression

Graphical Models as Block-Tree Graphs

Greedy Learning of Markov Network Structure

Greedy Sparsity-Constrained Optimization

Green's function based unparameterised multi-dimensional kernel density and likelihood ratio estimator

Ground Metric Learning

Group Lasso with Overlaps: the Latent Group Lasso approach

Group-based Query Learning for rapid diagnosis in time-critical situations