Vector Gaussian CEO Problem Under Logarithmic Loss and Applications

In this paper, we study the vector Gaussian Chief Executive Officer (CEO) problem under logarithmic loss distortion measure. Specifically, <inline-formula> <tex-math notation="LaTeX">{K} \geq 2 </tex-math></inline-formula> agents observe independently corrupted Gaus...

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Veröffentlicht in:	IEEE transactions on information theory Jg. 66; H. 7; S. 4183 - 4202
Hauptverfasser:	Ugur, Yigit, Aguerri, Inaki Estella, Zaidi, Abdellatif
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.07.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Institute of Electrical and Electronics Engineers
Schlagworte:	Algorithms Berger-Tung inner bound Blahut-Arimoto algorithm CEO problem Chief executive officers Codes Constraints Decoding Distortion Distortion measurement distributed source coding information bottleneck Information Theory logarithmic loss Loss measurement Machine learning Mathematical models Mathematics Multiterminal source coding Noise measurement Rate-distortion rate-distortion region Remote observing Source coding
ISSN:	0018-9448, 1557-9654
Online-Zugang:	Volltext
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