The technique presented here achieves simultaneous optimization of schedule time and data path component cost within a structured data path architecture, using a genetic algorithm...
Online learning and kernel learning are two active research topics in machine learning. Although each of them has been studied extensively, there is a limited effort in addressing ...
We present a polynomial-time algorithm that provably recovers the signer's secret DSA key when a few bits of the random nonces k (used at each signature generation) are known ...
Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
We study the asymptotic behavior at infinity of solutions of a second order evolution equation with linear damping and convex potential. The differential system is defined in a rea...