There is a profound optimism on the impact of deep learning (DL) and AI in the sciences with Geoffrey Hinton concluding that 'They should stop educating radiologists now'. However, DL has an Achilles heel: it is universally unstable so that small changes in the initial data can lead to large errors in the final result. This has been documented...
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Previous Seminars
On the foundations of computational mathematics, Smale’s 18th problem and the potential limits of AI
On the foundations of computational mathematics, Smale’s 18th problem and the potential limits of AI
Wed, Jul 15, 2020, 12:00 pm
Speaker(s):
Anders Hansen
University of Cambridge)
Trainability and accuracy of artificial neural networks
Wed, Jul 8, 2020, 12:00 pm
Speaker(s):
Eric Vanden-Eijnden
Courant Institute, NYU
Towards a mathematical understanding of supervised learning: What we know and what we don't know
Wed, Jul 1, 2020, 12:00 pm
Speaker(s):
Weinan E
Department of Mathematics and Program in Applied and Computational Mathematics
Reimagining Digitized Newspapers with Machine Learning
Fri, May 15, 2020, 11:30 am
Speaker(s):
Ben Lee
Library of Congress Innovator-in-Residence
Newspaper Navigator: Reimagining Digitized Newspapers with Machine Learning
Running and Analyzing Large-scale Psychology Experiments
Fri, Mar 6, 2020, 12:00 pm
Speaker(s):
Princeton University
Preference Modeling with Context-Dependent Salient Features
Mon, Feb 24, 2020, 4:00 pm
Speaker(s):
LAURA BALZANO
UNIVERSITY OF MICHIGAN
Preference Modeling with Context-Dependent Salient Features
Massively Parallel Evolutionary Computation for Empowering Electoral Reform
Fri, Feb 21, 2020, 12:15 pm
Speaker(s):
Wendy Tam Cho
UIUC, Politics/Computer Science
Wearable Brain-Machine Interface Architectures for Neurocognitive Stress
Mon, Feb 10, 2020, 4:30 pm
Speaker(s):
Rose Faghih
University of Houston
Scalable Semidefinite Programming
Mon, Feb 10, 2020, 4:00 pm
Speaker(s):
Madeleine Udell
Cornell University
Targeted Machine Learning for Causal Inference
Fri, Feb 7, 2020, 12:00 pm
Speaker(s):
Mark van der Laan
UC Berkeley, Biostatistics/Statistics