Technical Program

L.2: Classification

Session Type: Lecture
Track: Statistics and Learning Theory
Virtual Session: View on Virtual Platform
Session Chair: Lalitha Sankar, Arizona State University
 
L.2.1: Evaluation of Error Probability of Classification Based on the Analysis of the Bayes Code
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         Shota Saito; Waseda University
         Toshiyasu Matsushima; Waseda University
 
L.2.2: Optimality of Least-squares for Classification in Gaussian-Mixture Models
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         Hossein Taheri; University of California, Santa Barbara
         Ramtin Pedarsani; University of California, Santa Barbara
         Christos Thrampoulidis; University of California, Santa Barbara
 
L.2.3: A Fair Classifier Using Mutual Information
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         Jaewoong Cho; KAIST
         Gyeongjo Hwang; KAIST
         Changho Suh; KAIST
 
L.2.4: Analytic Study of Double Descent in Binary Classification: The Impact of Loss
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         Ganesh Ramachandra Kini; University of California, Santa Barbara
         Christos Thrampoulidis; University of California, Santa Barbara
 
L.2.5: On Binary Statistical Classification from Mismatched Empirically Observed Statistics
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         Hung-Wei Hsu; National Taiwan University, Taipei, Taiwan
         I-Hsiang Wang; National Taiwan University, Taipei, Taiwan
 

Plan Ahead

IEEE ISIT 2021

2021 IEEE International Symposium on Information Theory

11-16 July 2021 | Melbourne, Victoria, Australia

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