Finding Consensus Bayesian Network Structures

Finding Dense Clusters via "Low Rank + Sparse" Decomposition

Finding Exogenous Variables in Data with Many More Variables than Observations

Finding Non-overlapping Clusters for Generalized Inference Over Graphical Models

FINE: Fisher Information Non-parametric Embedding

Forest Density Estimation

Forest Garrote

Foundations of a Multi-way Spectral Clustering Framework for Hybrid Linear Modeling

From Data to the p-Adic or Ultrametric Model

From Sparse Signals to Sparse Residuals for Robust Sensing

Functional learning through kernels

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