The k-Nearest Neighbors algorithm can be easily adapted to classify complex objects (e.g. sets, graphs) as long as a proper dissimilarity function is given over an input space. Bo...
Adam Woznica, Alexandros Kalousis, Melanie Hilario
— We present a hybrid data mining approach to detect malicious executables. In this approach we identify important features of the malicious and benign executables. These feature...
Mohammad M. Masud, Latifur Khan, Bhavani M. Thurai...
— We describe an analog VLSI circuit implementing spike-driven synaptic plasticity, embedded in a network of integrate-and-fire neurons. This biologically inspired synapse is hi...
Typical approaches to multi-label classification problem require learning an independent classifier for every label from all the examples and features. This can become a computati...
An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of i...