We consider a specific kind of Abstract State Machines. It is shown how the machines can be used to provide a low-level formal semantics for a tiny object-oriented language, inclu...
In this work, we explore the use of a learning-based framework for retrieval of relevant mammogram images from a database, for purposes of aiding diagnoses. A fundamental issue is...
Issam El-Naqa, Yongyi Yang, Miles N. Wernick, Niko...
Objects model the world, and state is fundamental to a faithful modeling. Engineers use state machines to understand and reason about state transitions, but programming languages ...
Jonathan Aldrich, Joshua Sunshine, Darpan Saini, Z...
A simple, robust sliding-window part-of-speech tagger is presented and a method is given to estimate its parameters from an untagged corpus. Its performance is compared to a standa...
There has been much interest in unsupervised learning of hierarchical generative models such as deep belief networks. Scaling such models to full-sized, high-dimensional images re...
Honglak Lee, Roger Grosse, Rajesh Ranganath, Andre...