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CLSP Student Seminar

Submitted by Anonymous (not verified) on Thu, 10/28/2021 - 19:39

CLSP Student Seminar

Submitted by Anonymous (not verified) on Wed, 10/20/2021 - 04:27

CLSP Student Seminar

Submitted by Anonymous (not verified) on Tue, 10/05/2021 - 07:09

CLSP Student Seminar

Submitted by Anonymous (not verified) on Tue, 10/05/2021 - 07:09

IAA Seminar Series – Phil Thomas, UMass Amherst, “Safe and Fair Machine Learning: A Seldonian Approach”

Submitted by Anonymous (not verified) on Thu, 09/23/2021 - 14:58

Link to Recording
Abstract: Machine learning algorithms are everywhere, ranging from simple data analysis and pattern recognition tools used across the sciences to complex systems that achieve superhuman performance on various tasks. Ensuring that they are safe—that they do not, for example, cause harm to humans or act in a racist or sexist way—is therefore not a hypothetical problem to be dealt with in the future, but a pressing one that we can and should address now.

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