Biostatistics Fall Colloquium: Automated Model Building and Deep Learning

November 09, 2017
03:30 PM - 05:00 PM
Helen Wood Hall - Collins & Wilson Classroom 1W-502

Xiao Wang, PhD
Professor of Statistics, Purdue University

2017 Fall Colloquium

Title: Automated Model Building and Deep Learning

Abstract:  Analysis of big data demands computer aided or even automated model building. It becomes extremely difficult to analyze such data with traditional statistical models and model building methods. Deep learning has proved to be successful for a variety of challenging problems such as AlphaGo, driverless cars, and image classification. Understanding deep learning has however apparently been limited, which makes it difficult to be fully developed. In this talk, we focus on neural network models with one hidden layers. We provide an understanding of deep learning from an automated modeling perspective. This understanding leads to a sequential method of constructing deep learning models. This method is also adaptive to unknown underlying model structure. This is a joint work with Chuanhai Liu.

Sponsored by the Department of Biostatistics and Computational Biology
University of Rochester School of Medicine and Dentistry

Category: Talks