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QUANTISATION EFFECTS IN DISTRIBUTED OPTIMISATION

Abstract: 

In this presentation, the effects of quantisation on distributed convex optimisation algorithms are explored via the lens of monotone operator theory. Specifically, by representing transmission quantisation via an additive noise model, we demonstrate how quantisation can be viewed as an instance of an inexact Krasnoselskii-Mann scheme. In the case of two distributed solvers, the Alternating Direction Method of Multipliers and the Primal Dual Method of Multipliers, we further demonstrate how an adaptive quantisation scheme can be constructed to reduce transmission costs between nodes. Finally for the Gaussian channel capacity maximisation problem, we demonstrate convergence even in the presence of one-bit uniform quantisation based on the aforementioned adaptive quantisation scheme.

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Paper Details

Authors:
Richard Heusdens
Submitted On:
13 April 2018 - 4:27pm
Short Link:
Type:
Presentation Slides
Event:
Presenter's Name:
Joseph A.G. Jonkman
Paper Code:
SPCOM-L4.3
Document Year:
2018
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[1] Richard Heusdens, "QUANTISATION EFFECTS IN DISTRIBUTED OPTIMISATION", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/2764. Accessed: Oct. 17, 2018.
@article{2764-18,
url = {http://sigport.org/2764},
author = {Richard Heusdens },
publisher = {IEEE SigPort},
title = {QUANTISATION EFFECTS IN DISTRIBUTED OPTIMISATION},
year = {2018} }
TY - EJOUR
T1 - QUANTISATION EFFECTS IN DISTRIBUTED OPTIMISATION
AU - Richard Heusdens
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/2764
ER -
Richard Heusdens. (2018). QUANTISATION EFFECTS IN DISTRIBUTED OPTIMISATION. IEEE SigPort. http://sigport.org/2764
Richard Heusdens, 2018. QUANTISATION EFFECTS IN DISTRIBUTED OPTIMISATION. Available at: http://sigport.org/2764.
Richard Heusdens. (2018). "QUANTISATION EFFECTS IN DISTRIBUTED OPTIMISATION." Web.
1. Richard Heusdens. QUANTISATION EFFECTS IN DISTRIBUTED OPTIMISATION [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/2764