L.9: Learning Methods and Networks | |
Session Type: Lecture | |
Track: Statistics and Learning Theory | |
Virtual Session: View on Virtual Platform | |
Session Chair: Venugopal Veeravalli, University of Illinois at Urbana-Champaign | |
L.9.1: CodNN – Robust Neural Networks From Coded Classification | |
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Netanel Raviv; Washington University in Saint Louis | |
Siddharth Jain; California Institute of Technology | |
Pulakesh Upadhyaya; Texas A&M University | |
Jehoshua Bruck; California Institute of Technology | |
Anxiao Jiang; Texas A&M University | |
L.9.2: Functional Error Correction for Reliable Neural Networks | |
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Kunping Huang; Texas A&M University | |
Paul H. Siegel; University of California, San Diego | |
Anxiao Jiang; Texas A&M University | |
L.9.3: On the alpha-loss Landscape in the Logistic Model | |
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Tyler Sypherd; Arizona State University | |
Mario Diaz; Universidad Nacional Autónoma de México | |
Lalitha Sankar; Arizona State University | |
Gautam Dasarathy; Arizona State University | |
L.9.4: Max-affine Regression with Universal Parameter Estimation for Small-ball Designs | |
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Avishek Ghosh; University of California, Berkeley | |
Ashwin Pananjady; University of California, Berkeley | |
Kannan Ramchandran; University of California, Berkeley | |
Aditya Guntuboyina; University of California, Berkeley | |
L.9.5: Model Projection: Theory and Applications to Fair Machine Learning | |
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Wael Alghamdi; Harvard University | |
Shahab Asoodeh; Harvard University | |
Hao Wang; Harvard University | |
Flavio P. Calmon; Harvard University | |
Dennis Wei; IBM Research | |
Karthikeyan Natesan Ramamurthy; IBM Research | |
Plan Ahead
2021 IEEE International Symposium on Information Theory
11-16 July 2021 | Melbourne, Victoria, Australia