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Optimization Techniques for Deep Learning de Atefeh Hemmati

Optimization Techniques for Deep Learning: Springer Optimization and Its Applications, cartea 238

Autor Atefeh Hemmati, Amir Masoud Rahmani, Fatemeh Bazikar, Hossein Moosaei, Panos M. Pardalos
en Limba Engleză Hardback – 8 aug 2026

Din seria Springer Optimization and Its Applications

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Specificații

ISBN-13: 9783032207029
ISBN-10: 3032207029
Pagini: 208
Dimensiuni: 160 x 241 x 17 mm
Greutate: 0.43 kg
Editura: Springer
Colecția Springer Optimization and Its Applications
Seria Springer Optimization and Its Applications

Notă biografică

Atefeh Hemmati received her B.S. degree in Computer Engineering, Information Technology from Central Tehran Branch, IAU, Tehran, Iran in 2020 and received her M.S. degree in Computer Engineering, Software from the Science and Research Branch, IAU, Tehran, Iran in 2023. Her research interests include Internet of Things, LLMs, fog/cloud/edge computing, and artificial intelligence, especially in the fields of machine learning, deep learning. She has authored several publications in these fields
and actively contributes to advanced AI applications in IoT ecosystems.
Amir Masoud Rahmani received his B.S. in computer engineering from Amir Kabir University, Tehran, in 1996, his M.S. in computer engineering from Sharif University of Technology, Tehran, in 1998, and his Ph.D. in computer engineering from IAU University, Tehran, in 2005. Currently, he is a professor of computer engineering. His research interests include Machine Learning, the Internet of Things, cloud/fog computing, and artificial intelligence.
Fatemeh Bazikar received her B.S. degree in Applied Mathematics, Shahid Chamran University, Ahvaz, Iran, in 2011, her M.S. in Applied Mathematics (Optimization), Shahid Chamran University, Ahvaz, Iran, in 2013, her Ph.D. in Applied Mathematics, Guilan University, Rasht, Iran, in 2021, and her Postdoc Researcher in Department of Computer Science, Faculty of Mathematical Sciences, Alzahra University, Tehran, Iran, in 2024. Her research interests include Machine Learning, Optimization, Data Analysis, Mathematical Programming, and artificial intelligence, especially in the fields of machine learning.
Hossein Moosaei