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DTSTART;TZID=America/New_York:20211028T184500
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DTSTAMP:20240305T104709Z
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UID:10002894-1635446700-1635453900@cmsa.fas.harvard.edu
SUMMARY:ARCH: Know What Your Machine Doesn’t Know
DESCRIPTION:Speaker: Jie Yang\, Delft University of Technology \nTitle: ARCH: Know What Your Machine Doesn’t Know \nAbstract: Despite their impressive performance\, machine learning systems remain prohibitively unreliable in safety-\, trust-\, and ethically sensitive domains. Recent discussions in different sub-fields of AI have reached the consensus of knowledge need in machine learning; few discussions have touched upon the diagnosis of what knowledge is needed. In this talk\, I will present our ongoing work on ARCH\, a knowledge-driven\, human-centered\, and reasoning-based tool\, for diagnosing the unknowns of a machine learning system. ARCH leverages human intelligence to create domain knowledge required for a given task and to describe the internal behavior of a machine learning system; it infers the missing or incorrect knowledge of the system with the built-in probabilistic\, abductive reasoning engine. ARCH is a generic tool that can be applied to machine learning in different contexts. In the talk\, I will present several applications in which ARCH is currently being developed and tested\, including health\, finance\, and smart buildings.
URL:https://cmsa.fas.harvard.edu/event/10-28-2021-interdisciplinary-science-seminar/
CATEGORIES:Interdisciplinary Science Seminar
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