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Events for March 11, 2022
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CS Colloquium: Harsha V. Madhyastha (University of Michigan) - Inter-connecting society across space and time
Fri, Mar 11, 2022 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Harsha V. Madhyastha, University of Michigan
Talk Title: Inter-connecting society across space and time
Series: CS Colloquium
Abstract: Thanks to the Internet and a range of services that have been developed to take advantage of it -- web, email, social media, instant messaging, etc. -- being in the same place at the same time is no longer a requirement for all of us to share information with each other. Instead, we are able to store our ideas, opinions, and observations on services which enable others to access this information later from anywhere in the world.
In this talk, I will discuss my group/s work over the past several years to address some of the fundamental challenges faced by the providers of such global-scale services. I will provide examples of two broad research thrusts: 1) enabling cost-effective development and deployment of geo-distributed services, and 2) optimizing the availability and performance of client-service interactions. I will also briefly discuss my ongoing research in facilitating
information exchange in domains such as web archival, federated learning, and 3D printing.
This lecture satisfies requirements for CSCI 591: Research Colloquium
Biography: Harsha V. Madhyastha is an Associate Professor in CSE at the University of Michigan. His research broadly spans the areas of distributed systems and
networking. Two of his papers have received the IRTF's Applied Networking Research Prize, and he has also co-authored award papers at OSDI, NSDI, and IMC. He has received multiple Google Faculty Research awards, a NetApp Faculty Fellowship, a Facebook Faculty Award, and an NSF CAREER award.
Host: Barath Raghavan
Audiences: By invitation only.
Contact: Assistant to CS chair
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor.
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PhD Thesis Proposal - Aaron Chan
Fri, Mar 11, 2022 @ 03:00 PM - 05:00 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Candidate: Aaron Chan
Title: Generating and Utilizing Machine Explanations for Trustworthy NLP
Time: Friday, March 11, 3:00PM-5:00PM PST
Committee: Xiang Ren, Robin Jia, Jesse Thomason, Bistra Dilkina, Morteza Dehghani
Abstract:
Neural language models (NLMs) have achieved remarkable success on a wide range of natural language processing (NLP) tasks. However, NLMs sometimes exhibit undesirable behavior, which can be difficult to resolve due to NLMs' opaque reasoning processes. Such a lack of transparency poses serious concerns about NLMs' trustworthiness in high-stakes decision-making.
This motivates the use of machine explanations to automatically interpret how NLMs make decisions. In my thesis proposal, I argue that building human trust in NLP systems requires being able to: (A) generate machine explanations for NLM behavior faithfully and plausibly, and (B) utilize machine explanations to improve language model decision-making.
First, I introduce a framework for optimizing machine explanations w.r.t. both faithfulness and plausibility, without compromising the NLM's task performance. Second, I present an algorithm for regularizing NLMs via machine explanations, in order to improve NLM task performance. Third, I discuss using limited human-in-the-loop feedback on machine explanations to further improve NLMs' generalization ability.
Zoom Link: https://usc.zoom.us/j/99570395469?pwd=OE9IMnhLOU5oSmRCYzFiUWdMZ1BuZz09WebCast Link: https://usc.zoom.us/j/99570395469?pwd=OE9IMnhLOU5oSmRCYzFiUWdMZ1BuZz09
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
This event is open to all eligible individuals. USC Viterbi operates all of its activities consistent with the University's Notice of Non-Discrimination. Eligibility is not determined based on race, sex, ethnicity, sexual orientation, or any other prohibited factor.
