Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. In this pap...
Conditional Random Fields (CRFs; Lafferty, McCallum, & Pereira, 2001) provide a flexible and powerful model for learning to assign labels to elements of sequences in such appl...
Thomas G. Dietterich, Adam Ashenfelter, Yaroslav B...
In this paper we introduce Ant-Q, a family of algorithms which present many similarities with Q-learning (Watkins, 1989), and which we apply to the solution of symmetric and asymm...
Model checking is emerging as a popular technology for reasoning about behavioral properties of a wide variety of software artifacts including: requirements models, architectural ...
We address the problem of fast and accurate localization of miniature surgical instruments like needles or electrodes using 3D ultrasound (US). An algorithm based on maximizing a ...