01943nam 2200385 450 991055401720332120230417144515.01-66543-166-0(CKB)4100000012022102(NjHacI)994100000012022102(EXLCZ)99410000001202210220230417d2021 uy 0engur|||||||||||txtrdacontentcrdamediacrrdacarrier2021 ACM/IEEE 3rd Workshop on Machine Learning for CAD (MLCAD) /Institute of Electrical and Electronics EngineersPiscataway, New Jersey :IEEE,[2021]©20211 online resource (125 pages) illustrations1-66543-167-9 The objective of the International Workshop on Machine Learning for CAD (MLCAD) is to provide educational and technical enrichment for Machine Learning techniques for Computer Aided Design (CAD) and to promote the state of the art advancement MLACD is a forum for an in depth technical discussion and platform for exploring new ideas and research topics with respect to topics relevant to the CAD industry ML for system level design ML approaches to logic design ML for physical design ML for analog design ML for power and thermal management ML for Design Technology Co Optimization (DTCO) ML methods to predict aging and reliability Labeled and unlabeled data in ML for CAD ML techniques for resource management in many cores ML for Verification and Validation.2021 ACM/IEEE 3rd Workshop on Machine Learning for CAD Computer-aided designCongressesMachine learningCongressesComputer-aided designMachine learning620.00420285NjHacINjHaclPROCEEDING99105540172033212021 ACM2124484UNINA