Many activity dependent learning rules have been proposed in order to model long-term potentiation (LTP). Our aim is to derive a spike time dependent learning rule from a probabili...
Jean-Pascal Pfister, David Barber, Wulfram Gerstne...
This paper explores the effect of initial weight selection on feed-forward networks learning simple functions with the back-propagation technique. We first demonstrate, through th...
We study the problem of monotonicity testing over the hypercube. As previously observed in several works, a positive answer to a natural question about routing properties of the hy...
We study an extension of the "standard" learning models to settings where observing the value of an attribute has an associated cost (which might be different for differ...
This paper presents a novel approach for the synthesis of dynamic CMOS circuits using Domino and Nora styles. As these logic styles can implement only non-inverting logic, convent...