We present an algorithm to generate samples from probability distributions on the space of curves. Traditional curve evolution methods use gradient descent to find a local minimum...
Ayres C. Fan, John W. Fisher III, Jonathan Kane, A...
Recent work has exploited boundedness of data in the unsupervised learning of new types of generative model. For nonnegative data it was recently shown that the maximum-entropy ge...
Klaim is an experimental language designed for modeling and programming distributed systems composed of mobile components where distribution awareness and dynamic system architect...
Rocco De Nicola, Joost-Pieter Katoen, Diego Latell...
Intuitively, any `bag of words' approach in IR should benefit from taking term dependencies into account. Unfortunately, for years the results of exploiting such dependencies ...
Eduard Hoenkamp, Peter Bruza, Dawei Song, Qiang Hu...
Accountability mechanisms, which rely on after-the-fact verification, are an attractive means to enforce authorization policies. In this paper, we describe an operational model of ...
Radha Jagadeesan, Alan Jeffrey, Corin Pitcher, Jam...