An Introduction to Conditional Random Fields
An Iterative Algorithm for Fitting Nonconvex Penalized Generalized Linear Models with Grouped Predictors
Analysis of a Random Forests Model
Analysis of boosting algorithms using the smooth margin function
AOSO-LogitBoost: Adaptive One-Vs-One LogitBoost for Multi-Class Problem
Application of Bayesian Hierarchical Prior Modeling to Sparse Channel Estimation
Approximate Gaussian Integration using Expectation Propagation
Asymptotic Accuracy of Distribution-Based Estimation for Latent Variables
Asymptotic Confidence Sets for General Nonparametric Regression and Classification by Regularized Kernel Methods
Asymptotic Normality of Support Vector Machine Variants and Other Regularized Kernel Methods
Asynchronous Stochastic Approximation with Differential Inclusions
Auto-associative models, nonlinear Principal component analysis, manifolds and projection pursuit
Automatic Relevance Determination in Nonnegative Matrix Factorization with the β-Divergence
Autoregressive Kernels For Time Series
Bayesian Active Learning for Classification and Preference Learning
Bayesian Agglomerative Clustering with Coalescents
Bayesian Causal Induction
Bayesian Classification and Regression with High Dimensional Features
Bayesian Group Factor Analysis
Bayesian inference for queueing networks and modeling of internet services