[Lecture] From Rosenblatt’s Perceptron to Support Vector Machine
Wednesday, April 7, 2021
11:00 am - 12:00 pm
Online via Zoom. Contact Dr. Nouhad Rizk at firstname.lastname@example.org for the link.
One of the influential ideas in machine learning was Rosenblatt’s Perceptron. In this talk, we start with the history of data classification and describe details of Rosenblatt’s Perceptron idea. Then we extend this idea to understand the details of the Support Vector Machine (SVM) developed by Vladimir Vapnik and colleagues at AT&T Bell Laboratories back in the 90s. Then, we learn about the soft-margin classification, primal and dual formalization, and use it to understand the kernel trick in SVM. During the talk, we will show these ideas using from scratch python and Spark implementation of these perceptron and SVM ideas.
About the Speaker
Kia Teymourian is an assistant professor in the Department of Computer Science of Boston University Metropolitan College, where he has been since 2017 teaching courses related to data analysis and Big Data processing, as well as software engineering. From 2014 to 2017 he worked as a postdoctoral research associate at the department of computer science at Rice University.
Dr. Teymourian holds a BSc and MSc degree from Berlin University of Technology (TU-Berlin) and a PhD from Freie Universität Berlin. His research interest lies in extended database technologies, data stream processing, big data analytics, as well as web and text mining. He has published more than 40 publications in these fields and made important contributions to multiple large and international research projects, including several funded by the European Commission, the German Federal Ministry of Education and Research (BMBF), and the DARPA Pliny Project at Rice University.