Our goal is to fit the multiple instances (or structures) of a generic model existing in data. Here we propose a novel model selection scheme to estimate the number of genuine str...
Multi-task learning refers to the learning problem of performing inference by jointly considering multiple related tasks. There have already been many research efforts on supervise...
k-Anonymity protects privacy by ensuring that data cannot be linked to a single individual. In a k-anonymous dataset, any identifying information occurs in at least k tuples. Much...
Mehmet Ercan Nergiz, Chris Clifton, A. Erhan Nergi...
In this paper, we propose a general-purpose methodology for detecting multiple objects with known visual models from multiple views. The proposed method is based Monte-Carlo sampli...
Applications that span multiple virtual organizations (VOs) are of great interest to the eScience community. However, recent attempts to execute large-scale parameter sweep applic...
Shahaan Ayyub, David Abramson, Colin Enticott, Sla...