Inferring Latent Structure From Mixed Real and Categorical Relational Data
Abstract
We consider analysis of relational data (a matrix), in which the rows correspond to subjects (e.g., people) and the columns correspond to attributes. The elements of the matrix may be a mix of real and categorical. Each subject and attribute is characterized by a latent binary feature vector, and an inferred matrix maps each row-column pair of binary feature vectors to an observed matrix element. The latent binary features of the rows are modeled via a multivariate Gaussian distribution with low-rank covariance matrix, and the Gaussian random variables are mapped to latent binary features via a probit link. The same type construction is applied jointly to the columns. The model infers latent, low-dimensional binary features associated with each row and each column, as well correlation structure between all rows and between all columns.
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Scholars@Duke

Lawrence Carin
Lawrence Carin earned the BS, MS, and PhD degrees in electrical engineering at the University of Maryland, College Park, in 1985, 1986, and 1989, respectively. In 1989 he joined the Electrical Engineering Department at Brooklyn Polytechnic Institute (now part of NYU) as an Assistant Professor, and became an Associate Professor there in 1994. In September 1995 he joined the Electrical and Computer Engineering (ECE) Department at Duke University, where he is now a Professor. He was ECE Department Chair from 2011-2014, and Vice Provost and Vice President for Research from 2014-2020. He was the Provost at King Abdullah University of Science & Technology (KAUST) from 2020-2023, returning to Duke in 2023. From 2003-2014 he held the William H. Younger Distinguished Professorship, and since 2018 he has held the James L. Meriam Distinguished Professorship. Dr. Carin's research focuses on machine learning (ML) and artificial intelligence (AI). He publishes widely in the main ML/AI forums, and has addressed many applications of AI, including in medicine and security. He was co-founder of the small business Signal Innovations Group, which was acquired by BAE Systems in 2014, and in 2017 he co-founded the company Infinia ML, which was acquired by Aspirion in 2023. He is an IEEE Fellow.
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