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Aaron B. Wagner
Researcher at Cornell University
Publications - 161
Citations - 2987
Aaron B. Wagner is an academic researcher from Cornell University. The author has contributed to research in topics: Gaussian & Communication channel. The author has an hindex of 24, co-authored 151 publications receiving 2654 citations. Previous affiliations of Aaron B. Wagner include IBM & University of California, Davis.
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Rate Region of the Quadratic Gaussian Two-Encoder Source-Coding Problem
TL;DR: In this article, the authors determine the rate region of the quadratic Gaussian two-encoder source-coding problem, which is achieved by a simple architecture that separates the analog and digital aspects of the compression.
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Rate Region of the Quadratic Gaussian Two-Encoder Source-Coding Problem
TL;DR: The rate region of the quadratic Gaussian two-encoder source-coding problem is determined and the techniques can be used to determine the sum-rate of some generalizations of this classical problem.
Proceedings ArticleDOI
An operational measure of information leakage
TL;DR: Given two discrete random variables X and Y, an operational approach is undertaken to quantify the “leakage” of information from X to Y, and the resulting measure ℒ(X→Y ) is called maximal leakage, and is shown to be equal to the Sibson mutual information of order infinity.
Proceedings ArticleDOI
Rate Region of the Quadratic Gaussian Two-Encoder Source-Coding Problem
TL;DR: This work determines the rate region of the quadratic Gaussian two-encoder source-coding problem with separate distortion constraints and can be used to partially solve problems with more than two encoders or more general distortion constraints.
Journal ArticleDOI
On the Optimality of Binning for Distributed Hypothesis Testing
TL;DR: A distributed hypothesis testing problem in which data is compressed distributively and the detector seeks to decide between two possible distributions for the data is studied, showing that binning is optimal for a class of problems in which the goal is to “test against conditional independence.”