In k-means clustering we are given a set of n data points in d-dimensional space d and an integer k, and the problem is to determine a set of k points in d , called centers, to mi...
Tapas Kanungo, David M. Mount, Nathan S. Netanyahu...
Classifying an unknown input is a fundamental problem in pattern recognition. A common method is to define a distance metric between patterns and find the most similar pattern i...
Sung-Hyuk Cha, Charles C. Tappert, Sargur N. Sriha...
The balanced graph partitioning consists in dividing the vertices of an undirected graph into a given number of subsets of approximately equal size, such that the number of edges c...
— In this paper we present a new nature-inspired variation operator for binary encodings in genetic algorithms (GAs). Our method, called implicit alternative splicing (iAS), is r...
To help chemists design new drugs, we created a tool that uses interactive evolution to design drug molecules, the “Molecule Evoluator”. In contrast to most other evolutionary...
Eric-Wubbo Lameijer, Adriaan P. IJzerman, Joost N....