ECE Seminar Series – June 9 (Mon) @ 2:00 PM: "Nonlinear Transforms for Compression & Information Processing," Tsachy Weissman, Prof., EE, Stanford

Location: Engineering Science Building, Room 1001
Come at 1:30p for Cookies, Coffee and Conversation
DISTINGUISHED LECTURE at the ECE SEMINAR SERIES

Abstract

I will focus the talk on a variety of nonlinear transforms and their use for compression. The first is a "textual transform" sharing key properties with traditional transforms underlying much of our current multimedia compression technologies. It can form the basis for compression at bit rates until recently considered uselessly low, and for boosting human satisfaction from reconstructions at more traditional bit rates. The second is a "neural transform" - such as in the "implicit neural representation" framework - allowing to view the tension between compression ratio and neural network performance through the lens of rate-distortion theory and to develop information theoretically guided network pruning strategies. The third is a "Lempel-Ziv (LZ) transform", which can take any of a large class of compressors into new ones that share the main universality properties and computational grace of the Lempel-Ziv compressor. Collectively, these transforms give insight into achievable trade-offs between compression, accuracy and computation. This insight carries over to other information processing tasks such as classification, denoising and "GenAI". The talk is based in large part on joint work with Connor Ding, Abhiram Gorle, Jiwon Jeong and Naomi Sagan.

Bio

Tsachy Weissman is the Robert and Barbara Kleist Professor in the School of Engineering, and Professor of Electrical Engineering at Stanford University, where he has been on the faculty since 2003. His research and teaching focus on the science of information, with applications spanning genomics, neuroscience, and technology. He has been serving on editorial boards for scientific journals, technical advisory boards in industry, and as the Founding Director of the Stanford Compression Forum. His recent projects include the SHTEM summer internship program for high schoolers, the Starling initiative for data integrity, and Stagecast, a low-latency video platform allowing actors and singers to perform together in real-time while geographically distributed. He has received multiple awards for his research and teaching, including best paper awards from the IEEE Information Theory and Communications Societies, while his students received best student authored paper awards at the top conferences of their areas of scholarship. He has prototyped Guardant Health’s algorithms for early detection of cancer from blood tests, co-founded and sold Compressable to Amazon, and worked at AWS on reducing humanity’s cloud storage footprint via compression. His favourite gig to date was advising the HBO show Silicon Valley. He hates writing about himself in the third person

Hosted by: Distinguished Lecture at the ECE Seminar Series

Submitted by: Haewon Jeong <haewon@ece.ucsb.edu>