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Distance metric learning (DML) is successful in discovering intrinsic relations in data. However, most algorithms are computationally demanding when the problem size becomes large. In this paper, we propose a discriminative metric learning algorithm, develop a distributed scheme learning metrics on moderate-sized subsets of data, and aggregate the results into a global solution. The technique leverages...
Technologies and methods for the development of embedded system projects are highly constrained by predefined hardware and software platforms. In this sense, embedded system projects may have more goals (derived from constraints) to achieve than regular software projects. Without pragmatic support, engineers from different disciplines are likely to neglect some project goals in the real-world embedded...
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