Title :
Data mining in EDA - Basic principles, promises, and constraints
Author :
Wang, L.-C. ; Abadir, M.S.
Author_Institution :
Univ. of California at Santa Barbara, Santa Barbara, CA, USA
Abstract :
This paper discusses the basic principles of applying data mining in Electronic Design Automation. It begins by introducing several important concepts in statistical learning and summarizes different types of learning algorithms. Then, the experience of developing a practical data mining application is described, including promises that are demonstrated through positive results based on industrial settings and constraints explained in their respective application contexts.
Keywords :
data mining; electronic design automation; learning (artificial intelligence); EDA; data mining application; electronic design automation; industrial settings; statistical learning algorithm; Complexity theory; Computational modeling; Data mining; Data models; Kernel; Mathematical model; Support vector machines; Computer-Aided Design; Data Mining; Test; Verification;
Conference_Titel :
Design Automation Conference (DAC), 2014 51st ACM/EDAC/IEEE
Conference_Location :
San Francisco, CA
DOI :
10.1145/2593069.2596675
