ity Abstraction for Declarative Networking Applications Juan A. Navarro P?erez, Andrey Rybalchenko, and Atul Singh Max Planck Institute for Software Systems (MPI-SWS) Declarative N...
Andrey Rybalchenko, Atul Singh, Juan Antonio Navar...
This paper describes and evaluates privacy-friendly methods for extracting quasi-social networks from browser behavior on user-generated content sites, for the purpose of finding ...
Foster J. Provost, Brian Dalessandro, Rod Hook, Xi...
Mining discrete patterns in binary data is important for subsampling, compression, and clustering. We consider rankone binary matrix approximations that identify the dominant patt...
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...
One common predictive modeling challenge occurs in text mining problems is that the training data and the operational (testing) data are drawn from different underlying distributi...