+++ Machine Learning Seminar +++

Title: An Introduction to Deep Learning

Speaker: Prof. Lawrence Carin (Duke University)

Date and time: Jan 10, 2016 (2:00pm-3:00pm) 
Venue: RM Building, Room 101

Abstract: This talk will introduce Deep Learning from the perspective of generative statistical models, and factor analysis. We will see how the idea of sparsity in such models has a direct counterpoint in sigmoid belief networks, and other related models. The talk will explain how single-layer models of this type may naturally be extended to "deep" multi-layered settings. It will be demonstrated that for many applications (e.g., image and video analysis) convolutional factor models can be convenient, for which the convolutional neural networks have conventionally been used as a natural tool. We will finally see the usefulness of these deep models with a diverse set of applications.

Speaker bio: Lawrence Carin received the B.S., M.S., and Ph.D. degrees in electrical engineering from the University of Maryland, College Park, in 1985, 1986, and 1989, respectively. In 1989, he joined the Department of Electrical Engineering at Polytechnic University, Brooklyn, NY, as an Assistant Professor, where he became an Associate Professor in 1994. In 1995, he joined the Department of Electrical and Computer Engineering (ECE) at Duke University, where he is currently a Professor. He was the Chairman of the Duke ECE department from 2011 to 2014. He held the William H. Younger Distinguished Professorship from 2003 to 2013. He is a co-founder of Signal Innovations Group, Inc., a small business that was acquired by BAE Systems in 2014. Since 2014, he has been the Vice Provost of Research at Duke University. His research interests include machine learning and applied statistics. He has authored over 300 peer-reviewed papers, he an IEEE Fellow, and is a member of Tau Beta Pi and Eta Kappa Nu honor societies.