This paper is concerned with a specific brand of evolutionary algorithms: Memetic algorithms. A new local search technique with an adaptive neighborhood setting process is introdu...
Imbalanced data learning has recently begun to receive much attention from research and industrial communities as traditional machine learners no longer give satisfactory results. ...
Abstract— Aggregation of individual wavelengths into wavebands for their subsequent switching and routing as a single group is an attractive way for scalable and cost-efficient ...
Rauf Izmailov, Samrat Ganguly, Viktor Kleptsyn, Ai...
Optimizing the performance of shared-memory NUMA programs remains something of a black art, requiring that application writers possess deep understanding of their programs’ beha...
Abstract. This paper proposes a general local learning framework to effectively alleviate the complexities of classifier design by means of “divide and conquer” principle and ...