We propose a probabilistic latent variable model for unsupervised cluster matching, which is the task of finding correspondences between clusters of objects in different domains. Existing object matching methods find oneto-one matching. The proposed model finds many-tomany matching, and can handle multiple domains with different numbers of objects. The proposed model assumes that there are an i...

We propose a discriminative latent model for annotating images with unaligned object-level textual annotations. Instead of using the bag-of-words image representation currently popular in the computer vision community, our model explicitly captures more intricate relationships underlying visual and textual information. In particular, we model the mapping that translates image regions to annotat...

Two months of treatment with rifampin-pyrazinamide (RZ) and 9 months of treatment with isoniazid are both recommended for treatment of latent tuberculosis infection in adults without human immunodeficiency virus infection, but the relative cost-effectiveness of these 2 treatments is unknown. We used a Markov model to conduct a cost-effectiveness analysis to assess the impact on life expectancy ...

The paper proposes a spam filtering method that uses integrated and refined Latent Semantic Analysis (LSA) and Message-Digest Algorithm 5 (MD5) algorithms to address a series of universal problems in spam filtering, including remarkably lowered filtering precision and notably unbalanced filtering efficiency as a result of lack of latent semantic analysis of mail contents. In introducing LSA, it...

This paper investigates applying statistical topic models to extract and predict relationships between biological entities, especially protein mentions. A statistical topic model, Latent Dirichlet Allocation (LDA) is promising; however, it has not been investigated for such a task. In this paper, we apply the state-of-the-art Collapsed Variational Bayesian Inference and Gibbs Sampling inference...

It is widely known that spectral techniques are very effective for document retrieval. Recently, a lot of effort has been spent by researchers to provide a formal mathematical explanation for this effectiveness [3]. Latent Semantic Indexing, in particular, is a text retrieval algorithm based on the spectral analysis of the occurrences of terms in text documents. Despite of its value in improvin...

Toxoplasma infection in pregnant women may cause congenital toxoplasmosis. Diagnosis of infection is based on serological tests aimed at detecting IgM and IgG antibodies against Toxoplasma gondii. However, IgM antibodies are not an accurate marker for discriminating between acute and latent infection. Detection of residual or persistent IgM may occur months or even years after primary infection...