f-divergence estimation and two-sample homogeneity test under semiparametric density-ratio models

Faithfulness in Chain Graphs: The Gaussian Case

Falsification and future performance

Families of dendrograms

Fast Convergence Rate of Multiple Kernel Learning with Elastic-net Regularization

Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference

Fast global convergence of gradient methods for high-dimensional statistical recovery

Fast Inference of Interactions in Assemblies of Stochastic Integrate-and-Fire Neurons from Spike Recordings

Fast Learning Rate of lp-MKL and its Minimax Optimality

Fast Learning Rate of Multiple Kernel Learning: Trade-Off between Sparsity and Smoothness

Fast Learning Rate of Non-Sparse Multiple Kernel Learning and Optimal Regularization Strategies

Fast projections onto mixed-norm balls with applications

Fast Sparse Decomposition by Iterative Detection-Estimation

Fast, Linear Time Hierarchical Clustering using the Baire Metric

Fast, Linear Time, m-Adic Hierarchical Clustering for Search and Retrieval using the Baire Metric, with linkages to Generalized Ultrametrics, Hashing, Formal Concept Analysis, and Precision of Data Measurement

Feedback Message Passing for Inference in Gaussian Graphical Models

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