We address the problem of repairing large-scale biological networks and corresponding yet often discrepant measurements in order to predict unobserved variations. To this end, we ...
Martin Gebser, Carito Guziolowski, Mihail Ivanchev...
This paper presents a methodology for knowledge discovery from inherently distributed data without moving it from its original location, completely or partially, to other locations...
Diego M. Escalante, Miguel Angel Rodriguez, Antoni...
The advent of tagging and folksonomies for organizing shared resources on the social Web brought promising opportunities to help communities of users capture their knowledge. Howe...
Reinforcement learning (RL) is a fundamental process by which organisms learn to achieve a goal from interactions with the environment. Using Artificial Life techniques we derive ...
Yael Niv, Daphna Joel, Isaac Meilijson, Eytan Rupp...
We consider a networking subsystem for message–passing clusters that uses two unidirectional queues for data transfers between the network interface card (NIC) and the lower prot...