Taking into account input-model, input-parameter, and stochastic uncertainties inherent in many simulations, our Bayesian approach to input modeling yields valid point and confide...
Abstract. Training neural networks is a complex task of great importance in the supervised learning field of research. In this work we tackle this problem with five algorithms, a...
This paper presents an examination of two distinct but complementary extensions of previous work on hot spot contention in multistage interconnection networks. The first extensio...
Matthew K. Farrens, Brad Wetmore, Allison Woodruff
In this paper, the effect of the dimensionality of data sets on the exploitation of synergy among known nearest neighbor (NN) editing and condensing tools is analyzed using a synt...
Abstract— This paper describes our successful implementation of a robot that autonomously and strategically removes multiple blocks from an unstable Jenga tower. We present an in...
Jiuguang Wang, Philip Rogers, Lonnie Parker, Dougl...