Video: https://ieeetv.ieee.org/video/exploring-the-math-in-support-vector-machines

…Lagrange Multipliers,  Convex Hulls, Orthogonal Functions, Hilbert Space, Duality, Cover Theorem, …

Speaker:

Chapter Chair, Book Author, and SJSU Faculty Member,

Vishnu S. Pendyala, PhD

Date: October 4, 2022, 6:15 PM (PT)

Virtual Event via Zoom and YouTube live

Free Registration: https://www.eventbrite.com/e/exploring-the-math-in-support-vector-machines-tickets-425130124647

Synopsis:

“SVMs are a rare example of a methodology where geometric intuition, elegant mathematics, theoretical guarantees, and practical algorithms meet” – Bennet and Campbell

Support Vector Machines (SVMs) are used for supervised machine learning and have been successful in many applications including those like image classification that favor deep learning. SVM owes its power to the intriguing math involved in its fabrication. This talk will introduce SVM and cover some of that math. Topics covered will include constrained and unconstrained optimization, convexity, the general notion of a function space, minmax equilibrium, duality, Cover theorem, Kernels, and Mercer theorem.

Speaker Biography:

Dr. Vishnu S. Pendyala is a faculty member of the Department of Applied Data Science at San Jose State University and is the Chair of the IEEE Computer Society, Silicon Valley Chapter. He has over two decades of experience with software industry leaders like Cisco and Synopsys in the Silicon Valley, USA. During his recent 3-year term as an ACM Distinguished speaker and before that as a researcher and industry expert, he gave numerous (50+) invited talks. He holds MBA in Finance and PhD, MS, and BE degrees in Computer Engineering from US and Indian universities. Dr. Pendyala taught a one-week course sponsored by the Ministry of Human Resource Development (MHRD), Government of India, under the GIAN program in 2017 to Computer Science faculty from all over the country and delivered the keynote in a similar program sponsored by AICTE, Government of India in 2022.

Dr. Pendyala’s book, “Veracity of Big Data: Machine Learning and Other Approaches to Verifying Truthfulness” is catalogued by several libraries, including those of MIT, Stanford, CMU, and internationally. His edited books, “Tools and Techniques for Software Development in Large Organizations: Emerging Research and Opportunities” and “Machine Learning for Societal Improvement, Modernization, and Progress” are also well-received and are indexed by prominent libraries all over the world. Dr. Pendyala served on the Board of Directors, Silicon Valley Engineering Council during 2018-2019. He received the Ramanujan memorial gold medal at State Math Olympiad and has been a successful leader during his undergrad years. He also played an active role in Computer Society of India and was the Program Secretary for its annual national convention. Marquis Who’s Who has selected Pendyala’s biography for inclusion in multiple of its publications for multiple years. Dr. Pendyala spends his fast-vanishing spare time volunteering and has been a reviewer / judge for competitions like the Grace Hopper Celebration of Women in Computing, state level DECA, science fairs and other STEAM events for the last several years. He has traveled widely, covering ~30 states in the US and 23 countries. He resorts to yoga, spirituality, and listening to music, to unwind and be himself.