In this paper we propose the Possibilistic C-Means in Feature Space and the One-Cluster Possibilistic C-Means in Feature Space algorithms which are kernel methods for clustering in...
Maurizio Filippone, Francesco Masulli, Stefano Rov...
Many machine learning algorithms can be formulated in the framework of statistical independence such as the Hilbert Schmidt Independence Criterion. In this paper, we extend this c...
Xinhua Zhang, Le Song, Arthur Gretton, Alex J. Smo...
Abstract— Recently we proposed algorithms for concurrent execution on multiple clusters [9]. In this case, data partitioning is done at two levels; first, the data is distribute...
Chen Yu, Dan C. Marinescu, Howard Jay Siegel, John...
Current operating systems offer basic support for network interface controllers (NICs) supporting remote direct memory access (RDMA). Such support typically consists of a device d...
—Two strategies of distribution of computations can be used to implement parallel solvers for dense linear algebra problems for Heterogeneous Computational Clusters of Multicore ...