##Data Science Seminar##\\ Hosted by Department of Mathematical Sciences
* Date: Tuesday, April 17, 2018
* Time: 12:05pm -- 1:05pm
* Room: WH-100E
* Speaker: Wenbo Wang (Binghamton University)
* Title: A look at distance-weighted discrimination
**//Abstract//**
Distance-weighted discrimination (DWD) is a modern
margin-based classifier with an interesting geometric motivation. It
was proposed as a competitor to the support vector machine (SVM). The
authors greatly advance the current DWD methodology and its learning
theory. They propose a novel thrifty algorithm for solving standard
DWD and generalized DWD. Furthermore, they formulate a natural kernel
DWD approach in a reproducing kernel Hilbert space and then establish
the Bayes risk consistency of the kernel DWD by using a universal
kernel such as the Gaussian kernel.