We propose a new objective for network research: to build a fundamentally different sort of network that can assemble itself given high level instructions, reassemble itself as re...
David D. Clark, Craig Partridge, J. Christopher Ra...
Transfer learning is the ability of an agent to apply knowledge learned in previous tasks to new problems or domains. We approach this problem by focusing on model formulation, i....
We consider an architecture for a serverless distributed file system that does not assume mutual trust among the client computers. The system provides security, availability, and ...
William J. Bolosky, John R. Douceur, David Ely, Ma...
We develop geometric dynamical systems methods to determine how various components contribute to a neuronal network's emergent population behavior. The results clarify the mu...
The paper presents an approach to using structural descriptions, obtained through a human-robot tutoring dialogue, as labels for the visual object models a robot learns. The paper...
Geert-Jan M. Kruijff, John D. Kelleher, Gregor Ber...