Robust and Trustworthy Machine Learning Algorithms for Real Work Applications

Webcast

Wednesday, November 3, 2021 at 11am EDT | 8am PDT | 3pm GMT | 4pm CET JDeep learning algorithms have become a standard tool in many industries ranging from e-commerce to healthcare. Their ability to translate data into intelligent predictions completely transformed these industries, increasing productivity and controlling costs. These successes sometimes obscure inherent vulnerability of these models such as difficulty in generalizing in the presence of distribution shifts and ineffectiveness in estimating confidence of their prediction

Register free: http://www.pharmexec.com/pe/algorithms​

Event overview:

Deep learning algorithms have become a standard tool in many industries ranging from e-commerce to healthcare. Their ability to translate data into intelligent predictions completely transformed these industries, increasing productivity and controlling costs. These successes sometimes obscure inherent vulnerability of these models such as difficulty in generalizing in the presence of distribution shifts and ineffectiveness in estimating confidence of their prediction. In this webinar, the detail of these vulnerabilities will be illustrated and possible algorithmic solutions to these challenges will be described.

3 Key take-aways

  • Better understand the landscape of clinical AI applications
  • Identify some intrinsic vulnerabilities of these approaches
  • Learn about potential algorithmic solutions

Speakers

Regina Barzilay
Professor, Electrical Engineering and Computer Science Department
MIT

Regina Barzilay is a School of Engineering Distinguished Professor for AI and Health in the Department of Electrical Engineering and Computer Scienceand a member of the Computer Science and Artificial Intelligence Laboratory at the Massachusetts Institute of Technology. She is an AI faculty lead for Jameel Clinic, an MIT center for Machine Learning in Health.Her research interests are in natural language processing and applications of deep learning to chemistry and oncology. She is a recipient of various awards including the NSF Career Award, the MIT Technology Review TR-35 Award, Microsoft Faculty Fellowship and several Best Paper Awards at NAACL and ACL. In 2017, she received a MacArthur fellowship, an ACL fellowship and an AAAI fellowship. In 2021, she was awarded the Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity and the UNESCO/Netexplo Award. She received her PhD in Computer Science from Columbia University, and spent a year as a postdoc at Cornell University. Prof. Barzilay received her undergraduate degree from Ben-Gurion University of the Negev, Israel.

Register free: http://www.pharmexec.com/pe/algorithms​