Prerna Khurana

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In this work we propose a classification framework called class-wise deep dictionary learning (CWDDL). For each class, multiple levels of dictionaries are learnt using features from the previous level as inputs (for first level the input is the raw training sample). It is assumed that the cascaded dictionaries form a basis for expressing test samples for(More)
The deployment of smart meters by utilities holds the promise of improvements in operational efficiency, reliability and cost savings. With power measurements from smart meters, utilities can deploy innovative programs that allow end users to better control their energy usage while simultaneously reducing peak demand across the grid. In this paper, to(More)
Algorithms for sparse recovery problems from non-linear measurements have attracted some attention lately. Closely related to the problem of sparse is recovery is the problem of low-rank matrix recovery. There is no work on the topic of low-rank matrix recovery from non-linear measurements. This is the first study that proposes two algorithms for the said(More)
Ant colony optimization (ACO) is a P based metaheuristic algorithm which has been proven as a successful technique and applied to a number of combinatorial optimization problems and is also applied to the Traveling salesman problem (TSP). TSP is a well-known NP-complete combinatorial optimization (CO) problem and has an extensive application background. The(More)
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