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A Neyman - Pearson approach to universal erasure and list decoding
Pierre Moulin
Electrical and Computer Engineering
Beckman Institute for Advanced Science and Technology
Statistics
Information Trust Institute
Coordinated Science Lab
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Keyphrases
Neyman-Pearson
100%
Decoder
100%
List Decoding
100%
Erasure Decoding
100%
Weight Function
66%
Law
33%
Mutual Information
33%
Maximum mutual Information
33%
Sphere Packing
33%
Constant Composition
33%
Network Reliability
33%
Optimal Exponent
33%
Compound Classes
33%
Explicit Solution
33%
Error Exponent
33%
Symmetric Channel
33%
Random Codes
33%
Binary Symmetric Channel
33%
Fundamental Tradeoffs
33%
Threshold Rule
33%
Discrete Memoryless Channel
33%
Maximum a Posteriori Decoding
33%
Undetected Errors
33%
List Decoder
33%
Undetected Error Probability
33%
Mathematics
Mutual Information
100%
Weighting Functions
100%
Probability Theory
50%
Optimality
50%
Memoryless
50%
Posteriori
50%
Thresholding
50%
Explicit Solution
50%
Binary Symmetric Channel
50%
Random Code
50%
Engineering
Mutual Information
100%
Pearsons Linear Correlation Coefficient
100%
Optimality
50%
Simple Expression
50%
Maximum a Posteriori
50%
Explicit Solution
50%
Discrete Memoryless Channel
50%
Computer Science
Mutual Information
100%
Weighting Functions
100%
Neyman Pearson Approach
100%
Explicit Solution
50%
Binary Symmetric Channel
50%