Model reduction of large-scale linear time-invariant systems is an ubiquitous task in control and simulation of complex dynamical processes. We discuss how LQG balanced truncation ...
Many problems of theoretical and practical interest can be formulated as Constraint Satisfaction Problems (CSPs). The general CSP is known to be NP-complete; however, distributed m...
Montserrat Abril, Miguel A. Salido, Federico Barbe...
Practical data mining rarely falls exactly into the supervised learning scenario. Rather, the growing amount of unlabeled data poses a big challenge to large-scale semi-supervised...
We present a streaming framework for seamless building reconstruction from huge aerial LiDAR point sets. By storing data as stream files on hard disk and using main memory as only ...
Qian-Yi Zhou (University of Southern California), ...
We present an efficient implementation of an approximate balanced truncation model reduction technique for general large-scale RLC systems, described by a statespace model where t...