In kernel density estimation methods, an approximation of the data probability density function is achieved by locating a kernel function at each data location. The smoothness of ...
We consider the problem of bounded-error quantum state identification: given either state 0 or state 1, we are required to output `0', `1' or `?' ("don't ...
Dmitry Gavinsky, Julia Kempe, Oded Regev, Ronald d...
We introduce a graphical framework for Bayesian inference that is sufficiently general to accommodate not just the standard case but also recent proposals for a theory of quantum...
It is well known that general secure function evaluation (SFE) with information-theoretical (IT) security is infeasible in presence of a corrupted majority in the standard model. ...
This paper presents the Quantum-Dot Cellular Automata (QCA) physical design problem, in the context of the VLSI physical design problem. The problem is divided into three subprobl...
Dominic A. Antonelli, Danny Z. Chen, Timothy J. Dy...