This paper presents FC networks that are instantaneously trained neural networks that allow rapid learning of non-binary data. These networks, which generalize the earlier CC netw...
We describe an application of data mining and decision analysis to the problem of die-level functional test in integrated circuit manufacturing. Integrated circuits are fabricated...
This paper addresses the issue of policy evaluation in Markov Decision Processes, using linear function approximation. It provides a unified view of algorithms such as TD(), LSTD()...
Abstract. We extend the setting of Satisfiability Modulo Theories (SMT) by introducing a theory of costs C, where it is possible to model and reason about resource consumption and ...
Background: We have recently introduced a predictive framework for studying gene transcriptional regulation in simpler organisms using a novel supervised learning algorithm called...
Anshul Kundaje, Manuel Middendorf, Mihir Shah, Chr...