Quantum Machine Learning: Quantum Algorithms and Neural Networks (Quantum Computing)

ISBN 10: 3111342093 / ISBN 13: 9783111342092

Editore: De Gruyter, 2024

Codice articolo 18402090090

Riassunto:

Quantum computing has shown a potential to tackle specific types of problems, especially those involving a daunting number of variables, at an exponentially faster rate compared to classical computers. This volume focuses on quantum variants of machine learning algorithms, such as quantum neural networks, quantum reinforcement learning, quantum principal component analysis, quantum support vectors, quantum Boltzmann machines, and many more.

Informazioni sull?autore:

Pethuru Raj, PhD, is working as a chief architect at Reliance Jio Platforms Ltd. (JPL) Bangalore. Earlier, he worked with IBM Global Cloud Center of Excellence (CoE), Wipro Consulting Services (WCS), and Robert Bosch Corporate Research (CR). He has more than 22 years of IT industry experience and 8 years of research experience. He completed the Council of Scientific and Industrial Research (CSIR)- sponsored Ph.D. at Anna University, Chennai, and continued with the University Grants Commission (UGC)-sponsored postdoctoral research in the Department of
Computer Science and Automation, Indian Institute of Science (IISc), Bangalore. He has received a number of international research fellowships (JSPS and JST) to work as a research scientist for 3.5 years in two leading Japanese universities.
He focuses on some of the emerging technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), Model Optimization Techniques, Big, Fast and Streaming Analytics, Blockchain, Digital Twins, Cloud-Native Computing, Edge and Serverless Computing, Reliability Engineering, Microservices Architecture (MSA), Event-Driven Architecture (EDA), 5G, etc. More details are found in the following pages:
– Technology books: https://peterindia.net/MyBooks.html
– Google Scholar: https://scholar.google.co.in/citations?user=yaDflpYAAAAJ&hl=en
– The digital technologies and tools portal: www.peterindia.net/Digital.html

Houbing Herbert Song, PhD, is an Associate Professor whose research interests include cyber-physical systems/internet of things, cybersecurity and privacy, and AI/machine learning/big data analytics. His research has been sponsored by federal agencies (including National Science Foundation, US Department of Transportation, and Federal Aviation Administration, among others.) He is the Director of the NSF Center for Aviation Big Data Analytics (Planning), the Associate Director for Leadership of the DOT Transportation Cybersecurity Center for Advanced Research and Education (Tier 1 Center) and the Director of the Security and Optimization for Networked Globe Laboratory, SONG Lab, at UMBC. He serves as an Associate Editor for IEEE Transactions on Artificial Intelligence, IEEE Internet of Things Journal, IEEE Transactions on Intelligent Transportation Systems, and IEEE Journal on Miniaturization for Air and Space Systems. He received his Ph.D. degree in electrical engineering from the University of Virginia.

Dac-Nhuong Le received an MSc and PhD in computer science from Vietnam National University in 2009 and 2015, respectively. Presently, he is Associate Professor, Dean of Faculty of Information Technology, Haiphong University, Vietnam. He has been involved with academics including teaching and research since 2005. He has over 100+ papers published in SCI(E), Scopus international conferences, journals, and online book chapter contributions. He is researching the field of evolutionary computation, specializes in intelligence computing, evolutionary multi-objective optimization, network communication and security, cloud computing, IoT, VR/AR. Recently, he has been on the technique program committee, the technique reviews, the track chair for international conferences under Springer-ASIC/LNAI/CISC Series. He also has been servers in the editorial board of international journals and he authored, and edited over 25 computer science books by Springer, Wiley, CRC Press, IET, Bentham Publishing.

Narayan Vyas is an Assistant Professor in the Department of Computer Science and Application at Vivekananda Global University, Jaipur, India, where he is actively involved in research and development in computer science. He qualified for the NTA UGC NET & JRF on his first attempt, showcasing his academic excellence. He has extensive knowledge of the Internet of Things and Mobile Application Development and has provided training to students worldwide. He has published numerous articles in reputed, peer-reviewed national and international Scopus-indexed conferences and journals. Additionally, he has served as a keynote speaker and resource person for several workshops and webinars conducted in India. His research areas include Remote Sensing, the Internet of Things, Machine Learning, Deep Learning, and Computer Vision. He is an IEEE member and an active member of various international and national societies, such as IEEE Young Professionals, the Indian Society of Remote Sensing (ISRS), the IEEE Geosciences and Remote Sensing Society (GRSS), the IEEE Sensors Council, and the International Society of Photogrammetry and Remote Sensing (ISPRS). He has edited more than 10 books with various reputable publishers, including Wiley, DeGruyter, Apple Academic Press, and IGI Global.

Dati bibliografici

Titolo: Quantum Machine Learning: Quantum Algorithms...
Casa editrice: De Gruyter
Data di pubblicazione: 2024
Legatura: Rilegato
Condizione: New