Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...
A major difficulty for anomaly detection lies in discovering boundaries between normal and anomalous behavior, due to the deficiency of abnormal samples in the training phase. In...
Adaptive Memetic Algorithms couple an evolutionary algorithm with a number of local search heuristics for improving the evolving solutions. They are part of a broad family of meta...
— In this paper, we propose a new algorithm, named JACC-G, for large scale optimization problems. The motivation is to improve our previous work on grouping and adaptive weightin...
Zhenyu Yang, Jingqiao Zhang, Ke Tang, Xin Yao, Art...
Holland's Adaptation in Natural and Artificial Systems largely dealt with how systems, comprised of many self-interested entities, can and should adapt as a whole. This semin...
Robert E. Smith, Claudio Bonacina, Paul E. Kearney...