Suppose we observe samples of a subset of a collection of random variables. No additional information is provided about the number of latent variables, nor of the relationship between the latent and observed variables. Is it possible to discover the number of latent components, and to learn a statistical model over the entire collection of variables? We address this question in the setting in w...

Latent fingerprints are one of the most important and widely used evidence in law enforcement and forensic agencies worldwide. Yet, NIST evaluations show that the performance of state-of-the-art latent recognition systems is far from satisfactory. An automated latent fingerprint recognition system with high accuracy is essential to compare latents found at crime scenes to a large collection of ...

The optimal means for detecting and managing liver transplantation (LT) patients with latent tuberculosis (TB) are not well defined. Our study aims were to (1) determine the frequency and risk factors of latent TB in a large cohort of consecutive adult LT candidates and (2) determine the safety and efficacy of isoniazid treatment in LT recipients with latent TB. A review of patients assessed fo...

Transforming growth factor-beta (TGFbeta) is abundant in mammalian milk in a latent form. However, whether the latent form of TGFbeta in human milk is converted to the active form in vivo remains uncertain. To address this issue, we first investigated whether latent TGFbeta or human milk-borne latent TGFbeta was activated in an in vitro assay, simulating the effects of gastric acid. We then tes...

This chapter gives an overview of recent advances in latent variable analysis. Emphasis is placed on the strength of modeling obtained by using a flexible combination of continuous and categorical latent variables. To focus the discussion and make it manageable in scope, analysis of longitudinal data using growth models will be considered. Continuous latent variables are common in growth modeli...

For many applications, the observed data may be incomplete and there often exist variables that are unobserved but play an important role in capturing the underlying relationships. In this work, we propose a method to identify local latent variables and to determine their structural relations with the observed variables. We formulate the local latent variable discovery as discovering the Markov...

This paper focuses on service clustering and uses service descriptions to construct probabilistic models for service clustering. We discuss how service descriptions can be enriched with machine-interpretable semantics and then we investigate how these service descriptions can be grouped in clusters in order to make discovery, ranking, and recommendation faster and more effective. We propose usi...

GARP/LRRC32 was defined as a marker of activated human regulatory T cells (Tregs) that is responsible for surface localization of latent TGF-b1. We find that GARP and latent TGF-b1 are also found on mouse Tregs activated via TCR stimulation; however, in contrast to human Tregs, GARP is also expressed at a low level on resting Tregs. The expression of GARP can be upregulated on mouse Tregs by IL...