This paper presents a novel nonlinear dictionary learning (DL) model to address the energy
disaggregation (ED) problem, ie, decomposing the electricity signal of a home to its …

In this paper, we address the challenge of recovering an accurate breakdown of aggregated
tensor data using disaggregation examples. This problem is motivated by several …

Energy disaggregation is the task of discerning the energy consumption of individual
appliances from aggregated measurements, which holds promise for understanding and …

A tremendous growth in data collection has been an important enabler of the recent upsurge
in Machine Learning (ML) models. ML techniques involve processing, analyzing, and …