19 citations · 32 across the 4 of their papers we have counts for
4 papers
Decentralized Data Reduction with Quantization Constraints
Ge Xu, Shengyu Zhu, Biao Chen
A guiding principle for data reduction in statistical inference is the sufficiency principle. This paper extends the classical sufficiency principle to decentralized inference, i.e…
Wyner's Common Information: Generalizations and A New Lossy Source Coding Interpretation
Ge Xu, Wei Liu, Biao Chen
Wyner's common information was originally defined for a pair of dependent discrete random variables. Its significance is largely reflected in, hence also confined to, several exist…
The Sufficiency Principle for Decentralized Data Reduction
Ge Xu, Biao Chen
This paper develops the sufficiency principle suitable for data reduction in decentralized inference systems. Both parallel and tandem networks are studied and we focus on the case…
The Common Information of N Dependent Random Variables
Wei Liu, Ge Xu, Biao Chen
This paper generalizes Wyner's definition of common information of a pair of random variables to that of random variables. We prove coding theorems that show the same operation…