We propose a new transductive learning algorithm for learning optimal linear representations that utilizes unlabeled data. We pose the problem of learning linear representations a...
To address the productivity bottlenecks in power analysis and optimization of modern systems, we propose to treat power as a signal and leverage the rich set of signal processing ...
This paper studies TSV-to-TSV coupling in 3D ICs. A full-chip SI analysis flow is proposed based on the proposed coupling model. Analysis results show that TSVs cause significan...
Chang Liu, Taigon Song, Jonghyun Cho, Joohee Kim, ...
In this paper we develop a methodology for defining stopping rules in a general class of global random search algorithms that are based on the use of statistical procedures. To bu...
In this paper, we propose a new approach for VLSI interconnect global routing that can optimize both congestion and delay, which are often competing objectives. Our approach provi...