We apply a scalable approach for practical, comprehensive design space evaluation and optimization. This approach combines design space sampling and statistical inference to ident...
All existing methods for thermal-via allocation are based on a steady-state thermal analysis and may lead to excessive number of thermal vias. This paper develops an accurate and ...
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...
This article presents novel results concerning the recovery of signals from undersampled data in the common situation where such signals are not sparse in an orthonormal basis or ...
Many combinatorial optimization problems in biosequence analysis are solved via dynamic programming. To increase programming productivity and program reliability, a domain specifi...