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Optimal grouping for group minimax hypothesis testing
Kush R. Varshney,
Lav R. Varshney
National Center for Supercomputing Applications (NCSA)
Industrial and Enterprise Systems Engineering
Coordinated Science Lab
Beckman Institute for Advanced Science and Technology
Carl R. Woese Institute for Genomic Biology
Neuroscience Program
Electrical and Computer Engineering
Siebel School of Computing and Data Science
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Keyphrases
Minimax
100%
Minimax Hypothesis Testing
100%
Optimal Grouping
100%
Prior Probability
60%
Divergence
40%
Bayes Risk
40%
Bayesian Hypothesis Testing
40%
Detection Performance
20%
Centroid
20%
Rate-distortion
20%
Novel Intermediate
20%
Detection Scheme
20%
Detecting Signals
20%
Optimal Representation
20%
Additive White Gaussian Noise
20%
Asymptotic Analysis
20%
Voronoi Diagram
20%
Optimal Partition
20%
Number of Groups
20%
Intermediates Identification
20%
Distributed Signals
20%
Distortion Type
20%
Bregman Divergence
20%
Bregman
20%
ENet
20%
Mathematics
Minimax
100%
Statistical Hypothesis Testing
100%
Prior Probability
37%
Bayes Risk
25%
Bayesian
12%
Asymptotic Analysis
12%
Centroid
12%
Bayesian Hypothesis Testing
12%
Point Representation
12%
Random Noise
12%