Distributed data mining deals with the problem of data analysis in environments with distributed data, computing nodes, and users. Peer-to-peer computing is emerging as a new dist...
Souptik Datta, Kanishka Bhaduri, Chris Giannella, ...
In recent years, spectral clustering method has gained attentions because of its superior performance compared to other traditional clustering algorithms such as K-means algorithm...
Fuzzy clustering is well known as a robust and efficient way to reduce computation cost to obtain the better results. In the literature, many robust fuzzy clustering models have be...
Mohammad Hossein Fazel Zarandi, Marzie Zarinbal, I...
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
Maximum margin clustering (MMC) has recently attracted considerable interests in both the data mining and machine learning communities. It first projects data samples to a kernel...