In this work we propose a comparative study of the effects of a continuous model update on the effectiveness of wellknown query recommendation algorithms. In their original formul...
Daniele Broccolo, Franco Maria Nardini, Raffaele P...
We investigate the problem of non-covariant behavior of policy gradient reinforcement learning algorithms. The policy gradient approach is amenable to analysis by information geom...
Convergence analysis of consensus algorithms is revisited in the light of the Hilbert distance. The Lyapunov function used in the early analysis by Tsitsiklis is shown to be the Hi...
Rodolphe Sepulchre, Alain Sarlette, Pierre Rouchon
It is desirable to find unusual data objects by Ramaswamy et al's distance-based outlier definition because only a metric distance function between two objects is required. It...
As the end of Moores-law is on the horizon, power becomes a limiting factor to continuous increases in performance gains for single-core processors. Processor engineers have shifte...