Constrained clustering has been well-studied for algorithms like K-means and hierarchical agglomerative clustering. However, how to encode constraints into spectral clustering rem...
Managing large-scale software projects involves a number of activities such as viewpoint extraction, feature detection, and requirements management, all of which require a human a...
Data clustering is a difficult problem due to the complex and heterogeneous natures of multidimensional data. To improve clustering accuracy, we propose a scheme to capture the lo...
Using the concept of discrete noiseless channels, it was shown by Shannon in A Mathematical Theory of Communication that the ultimate performance of an encoder for a constrained sy...
Several researchers have illustrated that constraints can improve the results of a variety of clustering algorithms. However, there can be a large variation in this improvement, e...