TU4.R4.3

A Unified Study on Sequentiality in Universal Classification with Empirically Observed Statistics

Ching-Fang Li, I-Hsiang Wang, National Taiwan University, Taiwan
Session:
Sequential Hypothesis Testing and Change Detection
Track:
11: Information Theory and Statistics
Location:
Omikron II
Presentation Time:
Tue, 9 Jul, 16:45 - 17:05
Session Chair:
I-Hsiang Wang, National Taiwan University
Presentation
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Discussion
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Session TU4.R4
TU4.R4.1: On the Optimal Tradeoffs among Error Exponents in Active Sequential Multiple Hypothesis Testing
Chia-Yu Hsu, I-Hsiang Wang, National Taiwan University, Taiwan
TU4.R4.2: Sequential Adversarial Hypothesis Testing
Eeshan Modak, Tata Institute of Fundamental Research, India; Mayank Bakshi, Arizona State University, United States; Bikash Kumar Dey, Indian Institute of Technology, Mumbai, India; Vinod M. Prabhakaran, Tata Institute of Fundamental Research, India
TU4.R4.3: A Unified Study on Sequentiality in Universal Classification with Empirically Observed Statistics
Ching-Fang Li, I-Hsiang Wang, National Taiwan University, Taiwan
TU4.R4.4: Joint Sequential Detection and Isolation of Anomalies under Composite Hypotheses
Anamitra Chaudhuri, Texas A&M University, United States; Georgios Fellouris, University of Illinois, Urbana-Champaign, United States
Resources
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