Nonnegative Matrix Factorization on Orthogonal Subspace
Pattern Recognition Letters
Semi-supervised distance metric learning for collaborative image retrieval and clustering
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Flexible constrained spectral clustering
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
A multi-objective optimisation approach for class imbalance learning
Pattern Recognition
Improving document clustering using automated machine translation
Proceedings of the 21st ACM international conference on Information and knowledge management
On constrained spectral clustering and its applications
Data Mining and Knowledge Discovery
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A historical survey of the origins of nonlinear programming is presented with emphasis placed on necessary conditions for optimality. The mathematical sources for the work of Karush, John, Kuhn, and Tucker are traced and compared. Their results are illustrated by duality theorems for nonlinear programs that antedate the modern development of the subject.