The paper takes a fresh look at algorithms for maximizing expected utility over a set of policies, that is, a set of possible ways of reacting to observations about an uncertain s...
In this survey paper we give an intuitive treatment of the discrete time quantization of classical Markov chains. Grover search and the quantum walk based search algorithms of Amba...
Background: Baum-Welch training is an expectation-maximisation algorithm for training the emission and transition probabilities of hidden Markov models in a fully automated way. I...
We propose a new algorithm to detect the presence and the localization of aliasing in a single digital image.Considering the image in Fourier domain, the fact that two frequencies...
In this paper, an invariant set of the weight of the perceptron trained by the perceptron training algorithm is defined and characterized. The dynamic range of the steady state va...
Charlotte Yuk-Fan Ho, Bingo Wing-Kuen Ling, Herber...