Mon, Jan 13, 2020 @ 11:00 AM - 12:00 PM
Conferences, Lectures, & Seminars
Speaker: Hal Daume, University of Maryland
Talk Title: Learning Language through Interaction
Series: CS Colloquium
Abstract: To have the broadest possible positive impact, machine learning-based natural language processing systems must be able to (a) learn when limited training data exists for the target tasks, languages (and varieties), and domains of interest, and (b) identify and mitigate potential harms in their use, in particular arising from the signals on which they are trained. I will first present new algorithms and applications for learning language processing systems through interaction with people, where implicit and/or explicit user feedback drives learning. I will then discuss learning challenges around "fairness" and how such interactive learning mechanisms can help address them.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Hal Daumé III is a Perotto Chair Professor in Computer Science and Language Science at the University of Maryland, and a Senior Principal Researcher at Microsoft Research. His research focuses on developing learning algorithms for natural language processing, with a focus on interactive learning methods, and techniques for mitigating harms that can arise from automated systems. He earned his Ph.D. from the University of Southern California in 2006, was an inaugural diversity and inclusion co-chair at NeurIPS 2018, is an action editor for TACL, and is program co-chair for ICML 2020.
Host: Fei Sha
Audiences: Everyone Is Invited
Posted By: Assistant to CS chair