In this work, we study the problem of within-network relational learning and inference, where models are learned on a partially labeled relational dataset and then are applied to ...
Monitoring and mining real-time network data streams is crucial for managing and operating data networks. The information that network operators desire to extract from the network...
Pere Barlet-Ros, Gianluca Iannaccone, Josep Sanju&...
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
A low-effort data mining approach to labeling network event records in a WLAN is proposed. The problem being addressed is often observed in an AI and data mining strategy to netwo...
Taghi M. Khoshgoftaar, Chris Seiffert, Naeem Seliy...
The responses of cortical neurons are often characterized by measuring their spectro-temporal receptive fields (strfs). The strf of a cell can be thought of as a representation of...
Martin Coath, Emili Balaguer-Ballester, Sue L. Den...