This paper examines important factors for link prediction in networks and provides a general, high-performance framework for the prediction task. Link prediction in sparse network...
Ryan Lichtenwalter, Jake T. Lussier, Nitesh V. Cha...
Modeling dynamical systems composed of aggregations of primitive proteins is critical to the field of astrobiological science, which studies early evolutionary structures dealing ...
Human visual capability has remained largely beyond the reach of engineered systems despite intensive study and considerable progress in problem understanding, algorithms and comp...
In this work an improvement of an initial approach to design Artificial Neural Networks to forecast Time Series is tackled, and the automatic process to design Artificial Neural N...
We show in this paper how several proposed Physical Unclonable Functions (PUFs) can be broken by numerical modeling attacks. Given a set of challenge-response pairs (CRPs) of a PU...