Technical Program

L.13: Online, Active, and Transfer Learning

Session Type: Lecture
Track: Statistics and Learning Theory
Virtual Session: View on Virtual Platform
Session Chair: Varun Jog, University of Wisconsin-Madison
 
L.13.1: Active Learning for Classification with Abstention
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         Shubhanshu Shekhar; University of California, San Diego
         Mohammad Ghavamzadeh; Facebook AI Research
         Tara Javidi; University of California, San Diego
 
L.13.2: Rényi Entropy Bounds on the Active Learning Cost-Performance Tradeoff
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         Vahid Jamali; University of Erlangen-Nuremberg, Germany
         Antonia Tulino; University of Napoli Federico II, Italy
         Jaime Llorca; New York University, New York
         Elza Erkip; New York University, New York
 
L.13.3: An Efficient Running Quantile Estimation Technique alongside Correntropy for Outlier Rejection in Online Regression
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         Sajjad Bahrami; University of California, Riverside
         Ertem Tuncel; University of California, Riverside
 
L.13.4: Information-theoretic analysis for transfer learning
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         Xuetong Wu; University of Melbourne
         Jonathan Manton; University of Melbourne
         Uwe Aickelin; University of Melbourne
         Jingge Zhu; University of Melbourne
 
L.13.5: What is the Value of Data? on Mathematical Methods for Data Quality Estimation
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         Netanel Raviv; Washington University in Saint Louis
         Siddharth Jain; California Institute of Technology
         Jehoshua Bruck; California Institute of Technology
 

Plan Ahead

IEEE ISIT 2021

2021 IEEE International Symposium on Information Theory

11-16 July 2021 | Melbourne, Victoria, Australia

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