Tomasz Trzcinski: Zero-waste machine learning

RISE Learning Machines Seminars gathers experts in AI for an open weekly seminar! Seminars include presentations on a current topic on machine learning. Every Thursday at 15 CET we invite you to listen presentations on current topics in machine learning research. Meet people and listen to AI experts at RISE as well as invited speakers from academia and industry from all over the world. Title: Zero-waste machine learning Speaker: Tomasz Trzcinski Abstract: Today, both science and industry rely heavily on machine learning models, predominantly artificial neural networks, that become increasingly complex and demand a significant amount of computational resources. The problem of model computational complexity is well known to the computer science community, yet existing methods typically attempt to solve it by shrinking the models, e.g. by quantizing them, or limiting their access to resources. In this talk, I will look holistically at the efficiency of machine learning models and draw the inspirations to address their main challenges from the green sustainable economy principles. Instead of constraining some computations or memory used by the models, I will focus on reusing what is available to them: computations done in the previous processing steps, partial information accessible at run-time, or knowledge gained by the model during previous training sessions in continually learned models. This new research path of zero-waste machine learning opens a plethora of research opportunities, both for academia and industry. About the speaker: Tomasz Trzciński (DSc, WUT'20; PhD, EPFL'14; MSc, UPC/PoliTo'10) is an Associate Professor at Warsaw University of Technology, where he leads a Computer Vision Lab, and at Jagiellonian University of Cracow (GMUM). He is also a Computer Vision Group Leader at IDEAS NCBR, a publicly-funded Polish Center for AI. He was a Visiting Scholar at Stanford University in 2017 and at Nanyang Technological University in 2019. Previously, he worked at Google in 2013, Qualcomm in 2012 and Telefónica in 2010. He is an Associate Editor of IEEE Access and MDPI Electronics and frequently serves as a reviewer in major computer science conferences (CVPR, ICCV, ECCV, NeurIPS, ICML) and journals (TPAMI, IJCV, CVIU). He is a Senior Member of IEEE, member of ELLIS Society, member of the ALICE Collaboration at CERN and an expert of National Science Centre and Foundation for Polish Science. He is a Chief Scientist at Tooploox and a co-founder of Comixify, a technology startup focused on using machine learning algorithms for video editing. Location: This is an online seminar. Connect using Zoom. Zoom link: https://rise.zoom.us/j/208117140