Process variations in modern VLSI technologies are growing in both magnitude and dimensionality. To assess performance variability, complex simulation and performance models param...
A dimension reduction method called Discrete Empirical Interpolation (DEIM) is proposed and shown to dramatically reduce the computational complexity of the popular Proper Orthogo...
Background: Kernel-based learning algorithms are among the most advanced machine learning methods and have been successfully applied to a variety of sequence classification tasks ...
Peter Meinicke, Maike Tech, Burkhard Morgenstern, ...
This paper treats the solution of nonlinear optimization problems involving discrete decision variables, also known as generalized disjunctive programming (GDP) or mixed-integer n...
Abstract— Community discovery has drawn significant research interests among researchers from many disciplines for its increasing application in multiple, disparate areas, inclu...
Haizheng Zhang, Baojun Qiu, C. Lee Giles, Henry C....