商品描述
This book offers a comprehensive guide to optimization techniques in deep learning, a transformative branch of artificial intelligence that has revolutionized fields from computer vision to healthcare. By bridging the gap between theoretical concepts and practical applications, it equips readers with the tools needed to harness the full potential of deep neural networks.
The chapters cover a wide range of optimization methods, beginning with the fundamentals of neural networks and key concepts of deep learning. Readers will explore critical topics such as gradient descent, stochastic optimization, and advanced algorithms, while also addressing the inherent challenges of optimization. The book delves into practical aspects, offering insights into how to make training deep models more efficient and stable. Emerging trends and future perspectives are also presented, making this work a must-read for anyone looking to stay at the forefront of the field.
This book is an invaluable resource for researchers and practitioners seeking practical solutions for optimizing neural networks. Students will find a clear path to understanding the principles and building theoretical knowledge, while industry professionals will gain insights into the latest techniques and trends. Whether you're a seasoned expert or new to the field, this book is essential for anyone interested in deep learning optimization.
商品描述(中文翻譯)
本書提供了深度學習優化技術的全面指南，這是一個變革性的人工智慧分支，已經徹底改變了從計算機視覺到醫療保健等領域。通過彌合理論概念與實際應用之間的差距，本書為讀者提供了利用深度神經網絡充分潛力所需的工具。
各章節涵蓋了廣泛的優化方法，從神經網絡的基本原理和深度學習的關鍵概念開始。讀者將探索關鍵主題，如梯度下降（gradient descent）、隨機優化（stochastic optimization）和先進算法，同時也會討論優化過程中固有的挑戰。本書深入探討實際方面，提供如何使深度模型訓練更高效和穩定的見解。新興趨勢和未來展望也在書中呈現，使這本書成為任何希望在該領域保持前沿的讀者必讀的作品。
本書對於尋求優化神經網絡的實用解決方案的研究人員和從業者來說，是一個無價的資源。學生將找到清晰的路徑來理解原則並建立理論知識，而行業專業人士則將獲得有關最新技術和趨勢的見解。無論您是資深專家還是該領域的新手，本書對於任何對深度學習優化感興趣的人來說都是必不可少的。
作者簡介
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 is an Associate Professor specializing in optimization, machine learning, and applied mathematics. He received his PhD in Applied Mathematics in 2013. His research spans optimization, machine learning, numerical analysis, biomedical applications, and scientific computing. He has authored over 60 publications in these fields and serves as a reviewer, guest editor, and editor for leading international journals. In addition, he has played a key role in organizing international conferences, contributing to the advancement of the global research community. Panos Pardalos is a Distinguished Emeritus Professor in the Department of Industrial and Systems Engineering at the University of Florida, and an affiliated faculty of Biomedical Engineering and Computer Science & Information; Engineering departments. Panos Pardalos is a world-renowned leader in Global Optimization, Mathematical Modeling, Energy Systems, Financial applications, and Data Sciences. He is a Fellow of AAAS, AAIA, AIMBE, EUROPT, and INFORMS and was awarded the 2013 Constantin Caratheodory Prize of the International Society of Global Optimization. In addition, Panos Pardalos has been awarded the 2013 EURO Gold Medal prize bestowed by the Association for European Operational Research Societies. This medal is the preeminent European award given to Operations Research (OR) professionals for "scientific contributions that stand the test of time." Panos Pardalos has been awarded a prestigious Humboldt Research Award (2018-2019). The Humboldt Research Award is granted in recognition of a researcher's entire achievements to date -fundamental discoveries, new theories, and insights that have had a significant impact on their discipline. Panos Pardalos is also a Member of several Academies of Sciences, and he holds several honorary degrees and affiliations. He is the Founding Editor of Optimization Letters, Energy Systems, and Co-Founder of the International Journal of Global Optimization, Computational Management Science, and Springer Nature Operations Research Forum. He has published over 600 journal papers, and edited/authored over 200 books. He is one of the most cited authors and has graduated 71 PhD students so far. Details can be found at www.ise.ufl.edu/pardalosPanos Pardalos has lectured and given invited keynote addresses worldwide in countries including, Australia, Azerbaijan, Belgium, Brazil, Canada, Chile, China, Cyprus, Czech Republic, Denmark, Egypt, England, France, Finland, Germany, Greece, Holland, Hong Kong, Hungary, Iceland, Ireland, Italy, Japan, Lithuania, Mexico, Mongolia, Montenegro, New Zealand, Norway, Peru, Portugal, Russia, South Korea, Singapore, Serbia, South Africa, Spain, Sweden, Switzerland, Taiwan, Turkey, Ukraine, United Arab Emirates, and the USA.
作者簡介(中文翻譯)
Atefeh Hemmati 於2020年在伊朗德黑蘭的伊朗伊斯蘭大學中央德黑蘭分校獲得計算機工程與資訊科技的學士學位，並於2023年在伊朗德黑蘭的伊朗伊斯蘭大學科學與研究分校獲得計算機工程與軟體的碩士學位。她的研究興趣包括物聯網、LLMs、雲端/霧端/邊緣計算以及人工智慧，特別是在機器學習和深度學習領域。她在這些領域發表了多篇論文，並積極貢獻於物聯網生態系中的先進人工智慧應用。Amir Masoud Rahmani 於1996年在德黑蘭的阿米爾卡比爾科技大學獲得計算機工程學士學位，1998年在德黑蘭的沙里夫科技大學獲得計算機工程碩士學位，並於2005年在伊朗伊斯蘭大學獲得計算機工程博士學位。目前，他是計算機工程的教授。他的研究興趣包括機器學習、物聯網、雲端/霧端計算以及人工智慧。Fatemeh Bazikar 於2011年在伊朗阿瓦士的沙希德查姆蘭大學獲得應用數學學士學位，2013年獲得應用數學（優化）碩士學位，2021年在伊朗拉什特的吉蘭大學獲得應用數學博士學位，並於2024年在伊朗德黑蘭的阿爾扎赫拉大學數學科學學院計算機科學系擔任博士後研究員。她的研究興趣包括機器學習、優化、數據分析、數學規劃以及人工智慧，特別是在機器學習領域。Hossein Moosaei 是一位專注於優化、機器學習和應用數學的副教授。他於2013年獲得應用數學博士學位。他的研究範疇包括優化、機器學習、數值分析、生物醫學應用和科學計算。他在這些領域發表了超過60篇論文，並擔任多本國際期刊的審稿人、客座編輯和編輯。此外，他在組織國際會議方面發揮了關鍵作用，為全球研究社群的發展做出了貢獻。Panos Pardalos 是佛羅里達大學工業與系統工程系的榮譽特聘教授，並且是生物醫學工程及計算機科學與資訊工程系的附屬教員。Panos Pardalos 是全球優化、數學建模、能源系統、金融應用和數據科學領域的世界知名領袖。他是美國科學促進會（AAAS）、美國人工智慧協會（AAIA）、美國醫學與生物工程學會（AIMBE）、歐洲優化協會（EUROPT）和運籌學會（INFORMS）的會士，並於2013年獲得國際全球優化學會的康斯坦丁·卡拉西奧多里獎。此外，Panos Pardalos 還獲得了2013年由歐洲運籌學會頒發的歐洲金獎，該獎項是頒發給運籌學（OR）專業人士的最高歐洲獎項，以表彰其「經得起時間考驗的科學貢獻」。Panos Pardalos 還獲得了2018-2019年著名的洪堡研究獎，該獎項是對研究者迄今為止整體成就的認可，包括基礎發現、新理論和對其學科有重大影響的見解。Panos Pardalos 也是多個科學學院的成員，並擁有多個榮譽學位和隸屬關係。他是《優化信件》、《能源系統》的創始編輯，並共同創辦了《國際全球優化期刊》、《計算管理科學》和《施普林格自然運籌學論壇》。他已發表超過600篇期刊論文，編輯/撰寫超過200本書籍。他是被引用次數最多的作者之一，至今已指導71名博士生。詳細資訊可參見 www.ise.ufl.edu/pardalos。Panos Pardalos 曾在全球多個國家進行演講和受邀主題演講，包括澳大利亞、阿塞拜疆、比利時、巴西、加拿大、智利、中國、塞浦路斯、捷克共和國、丹麥、埃及、英國、法國、芬蘭、德國、希臘、荷蘭、香港、匈牙利、冰島、愛爾蘭、意大利、日本、立陶宛、墨西哥、蒙古、黑山、新西蘭、挪威、秘魯、葡萄牙、俄羅斯、南韓、新加坡、塞爾維亞、南非、西班牙、瑞典、瑞士、台灣、土耳其、烏克蘭、阿聯酋和美國。
