@inproceedings{Shaloudegi:2016,
author = {Shaloudegi, K and Gyorgy, A and Szepesvari, C and Xu, W},
publisher = {Neutral Information Processing Systems Foundation, Inc.},
title = {SDP relaxation with randomized rounding for energy disaggregation},
url = {http://hdl.handle.net/10044/1/42314},
year = {2016}
}

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TY  - CPAPER
AB  - We develop a scalable, computationally efficient method for the task of energydisaggregation for home appliance monitoring. In this problem the goal is toestimate the energy consumption of each appliance over time based on the totalenergy-consumption signal of a household. The current state of the art is to modelthe problem as inference in factorial HMMs, and use quadratic programming tofind an approximate solution to the resulting quadratic integer program. Here wetake a more principled approach, better suited to integer programming problems,and find an approximate optimum by combining convex semidefinite relaxationsrandomized rounding, as well as a scalable ADMM method that exploits the specialstructure of the resulting semidefinite program. Simulation results both in syntheticand real-world datasets demonstrate the superiority of our method.
AU  - Shaloudegi,K
AU  - Gyorgy,A
AU  - Szepesvari,C
AU  - Xu,W
PB  - Neutral Information Processing Systems Foundation, Inc.
PY  - 2016///
TI  - SDP relaxation with randomized rounding for energy disaggregation
UR  - http://hdl.handle.net/10044/1/42314
ER  - 

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