Wang boyu (32 Ergebnisse)
Federated and Transfer Learning
Razavi-far, Roozbeh (EDT); Wang, Boyu (EDT); Taylor, Matthew E. (EDT); Yang, Qiang (EDT)
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Hardcover. Zustand: new. Hardcover. This book provides a collection of recent research works on learning from decentralized data, transferring information from one domain to another, and addressing theoretical issues on improving the privacy and incentive factors of federated learning as well as its connection with transfer lear…ning and reinforcement learning. Over the last few years, the machine learning community has become fascinated by federated and transfer learning. Transfer and federated learning have achieved great success and popularity in many different fields of application. The intended audience of this book is students and academics aiming to apply federated and transfer learning to solve different kinds of real-world problems, as well as scientists, researchers, and practitioners in AI industries, autonomous vehicles, and cyber-physical systems who wish to pursue new scientific innovations and update their knowledge on federated and transfer learning and their applications. This book provides a collection of recent research works on learning from decentralized data, transferring information from one domain to another, and addressing theoretical issues on improving the privacy and incentive factors of federated learning as well as its connection with transfer learning and reinforcement learning. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 380 | Sprache: Englisch | Produktart: Bücher | This book provides a collection of recent research works on learning from decentralized data, transferring information from one domain to another, and addressing theoretical issues on improving the privacy and incentive factors…of federated learning as well as its connection with transfer learning and reinforcement learning. Over the last few years, the machine learning community has become fascinated by federated and transfer learning. Transfer and federated learning have achieved great success and popularity in many different fields of application. The intended audience of this book is students and academics aiming to apply federated and transfer learning to solve different kinds of real-world problems, as well as scientists, researchers, and practitioners in AI industries, autonomous vehicles, and cyber-physical systems who wish to pursue new scientific innovations and update their knowledge on federated and transfer learning and their applications.
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Federated and Transfer Learning
Razavi-far, Roozbeh (EDT); Wang, Boyu (EDT); Taylor, Matthew E. (EDT); Yang, Qiang (EDT)
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Federated and Transfer Learning
Razavi-far, Roozbeh (EDT); Wang, Boyu (EDT); Taylor, Matthew E. (EDT); Yang, Qiang (EDT)
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Federated and Transfer Learning
Razavi-far, Roozbeh (EDT); Wang, Boyu (EDT); Taylor, Matthew E. (EDT); Yang, Qiang (EDT)
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Federated and Transfer Learning
Razavi-far, Roozbeh (EDT); Wang, Boyu (EDT); Taylor, Matthew E. (EDT); Yang, Qiang (EDT)
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Federated and Transfer Learning
Razavi-far, Roozbeh (EDT); Wang, Boyu (EDT); Taylor, Matthew E. (EDT); Yang, Qiang (EDT)
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Federated and Transfer Learning
Razavi-far, Roozbeh (EDT); Wang, Boyu (EDT); Taylor, Matthew E. (EDT); Yang, Qiang (EDT)
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Federated and Transfer Learning
Razavi-far, Roozbeh (EDT); Wang, Boyu (EDT); Taylor, Matthew E. (EDT); Yang, Qiang (EDT)
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Taschenbuch. Zustand: Neu. Federated and Transfer Learning | Roozbeh Razavi-Far (u. a.) | Taschenbuch | Adaptation, Learning, and Optimization | viii | Englisch | 2023 | Springer | EAN 9783031117503 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[do…t]com | Anbieter: preigu.
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a collection of recent research works on learning from decentralized data, transferring information from one domain to another, and addressing theoretical issues on improving the privacy and incentive factors of federated learning…as well as its connection with transfer learning and reinforcement learning. Over the last few years, the machine learning community has become fascinated by federated and transfer learning. Transfer and federated learning have achieved great success and popularity in many different fields of application. The intended audience of this book is students and academics aiming to apply federated and transfer learning to solve different kinds of real-world problems, as well as scientists, researchers, and practitioners in AI industries, autonomous vehicles, and cyber-physical systems who wish to pursue new scientific innovations and update their knowledge on federated and transfer learning and their applications.
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a collection of recent research works on learning from decentralized data, transferring information from one domain to another, and addressing theoretical issues on improving the privacy and incentive factors of federated learning as well… as its connection with transfer learning and reinforcement learning. Over the last few years, the machine learning community has become fascinated by federated and transfer learning. Transfer and federated learning have achieved great success and popularity in many different fields of application. The intended audience of this book is students and academics aiming to apply federated and transfer learning to solve different kinds of real-world problems, as well as scientists, researchers, and practitioners in AI industries, autonomous vehicles, and cyber-physical systems who wish to pursue new scientific innovations and update their knowledge on federated and transfer learning and their applications.
Federated and Transfer Learning
Razavi-far, Roozbeh (Editor)/ Wang, Boyu (Editor)/ Taylor, Matthew E. (Editor)/ Yang, Qiang (Editor)
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Hardcover. Zustand: new. Hardcover. This book provides a collection of recent research works on learning from decentralized data, transferring information from one domain to another, and addressing theoretical issues on improving the privacy and incentive factors of federated learning as well as its connection with transfer lear…ning and reinforcement learning. Over the last few years, the machine learning community has become fascinated by federated and transfer learning. Transfer and federated learning have achieved great success and popularity in many different fields of application. The intended audience of this book is students and academics aiming to apply federated and transfer learning to solve different kinds of real-world problems, as well as scientists, researchers, and practitioners in AI industries, autonomous vehicles, and cyber-physical systems who wish to pursue new scientific innovations and update their knowledge on federated and transfer learning and their applications. This book provides a collection of recent research works on learning from decentralized data, transferring information from one domain to another, and addressing theoretical issues on improving the privacy and incentive factors of federated learning as well as its connection with transfer learning and reinforcement learning. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Dialogues in Music - Africa Meets Asia: Proceedings of the 2005 and 2007 International Symposia on African and Chinese Music
ZHANG, Boyu [ed] & Kimasi L. Browne; Eric Charry; Cynthia Tse Kimberlin; Li Xin; Ming Yan; Timothy K. Njoora; John O. Robison; Wang Jianxin; Xiang Yang; Xiao Mei; Zhang Boyu; Zhang Zhentao; Zhou Qingqing
Verlag: Richmond CA: MRI Press, 2011
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Soft cover. Zustand: Near Fine. 1st Edition. 1stedn, English and Chinese Edition; 8vo illuswraps Softcover VG: xx+545pp, chin index, engl index, bibl; TOC: Dr. Kimasi Browne s Traditional China and African Diasporic Culture: Erhu, Apu, and the Gospel of Intercultural Exchange gives bibliographical information about the music exc…hange between Chinese Erhu and the Gospel music, and between the mission and objectives at CCOM and Azusa Pacific University (APU). Professor. Eric Charry s Cultural Revolution and African Music: Guinea and its Legacy discusses how the music is influenced by the country s leadership. Some of the points elucidate analysis on Chinese contemporary music. Dr. Cynthia Tse Kimberlin s The Eubanks Conservatory of Music and Arts illustrates how a music conservatory with a diverse international student body operates within a predominately African American middle class community in Los Angeles. It touches the methodology and the meaning of the multicultural music education. Dr. Timothy Njoora s Music and Meaning: Some Reflections Through Personal Compositions uses his own compositions to share his personal reflections on the construction of the personal and collective meaning-making throughout the composing process, and also relates the situation of professional composers in Africa. Professor. John Robison presents his paper From the Slums of Calcutta to the Concert Halls of London: The Life and Music of Indian Composer John Mayer (1930-2004) showing that similar approaches are also reflected in the personae and musical lives of both Chinese and African musicians. Professor Li Xin s paper My Understanding of African Pianism presents the author s own understanding of the piano works by Professor Akin Euba from Nigeria as well as by African-American composers. It reflects the methodologies used in researching music by Chinese scholars about their own music traditions as well as about researching traditions outside China. Professor Ming Yan s article Symphony of the Century-- The Cry after 100 Years of Chinese New Music deals with the concerns of the music situation in contemporary China. Professor Wang Jianxin s article Discipline Analysis of Qin Melodies says that it is important to analyze the process of Qin music making in order to understand Qin music. Professor Xiang Yang s article Kinship and the Inheritance of Music Customs focuses on the social and human relations in current rural communities formed by certain regional and blood ties within a relatively stable historical and continuous farming culture and society. Professor Xiao Mei presented her article Yue (music) Gathered in Shen (Body): An Incorporated Practice Perspective on Chinese Traditional Music . Apart from the composition-centered type of musicology, the development of Chinese traditional music has led to a holistic approach of the performer as the center, as well as the process, movement and function of the music. Professor Zhang Boyu's paper on Four Ways of Transformation in the Development of Chinese Traditional Music illustrates four situations of Chinese traditional music change: continuous traditional music, traditional music transforming from a lifestyle to an artistic form, traditional music transforming from a lifestyle to a cultural symbol, and completely professional traditional music. Professor Zhang Zhentao' paper An Historical Retrospective on Folk Arts Festivals - A Policy for the Preservation of Folk Music During the 20th Century looks at the staged festivals organized by the Chinese government as the agency to make Chinese folk art professional, modernized and urbanized. And finally Professor Zhou Qingqing article Variations of Shi Diao (fashionable tunes) in Han Folk Songs analyzes these tunes to illustrate the connections between the variations of each type of tune popular in different regions of China. (Description from "Note from the Editor", Zhang Boyu, Sept. 2010).
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a collection of recent research works on learning from decentralized data, transferring information from one domain to another, and addressing theoretical issues on improving the privacy and incentive factors of fed…erated learning as well as its connection with transfer learning and reinforcement learning. Over the last few years, the machine learning community has become fascinated by federated and transfer learning. Transfer and federated learning have achieved great success and popularity in many different fields of application. The intended audience of this book is students and academics aiming to apply federated and transfer learning to solve different kinds of real-world problems, as well as scientists, researchers, and practitioners in AI industries, autonomous vehicles, and cyber-physical systems who wish to pursue new scientific innovations and update their knowledge on federated and transfer learning and their applications. 380 pp. Englisch.
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Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a collection of recent research works on learning from decentralized data, transferring information from one domain to another, and addressing theoretical issues on improving the privacy and incentive factors of federated…learning as well as its connection with transfer learning and reinforcement learning. Over the last few years, the machine learning community has become fascinated by federated and transfer learning. Transfer and federated learning have achieved great success and popularity in many different fields of application. The intended audience of this book is students and academics aiming to apply federated and transfer learning to solve different kinds of real-world problems, as well as scientists, researchers, and practitioners in AI industries, autonomous vehicles, and cyber-physical systems who wish to pursue new scientific innovations and update their knowledge on federated and transfer learning and their applications. 380 pp. Englisch.
Sprache: Englisch
Verlag: Springer, Berlin|Springer International Publishing|Springer, 2023
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book provides a collection of recent research works on learning from decentralized data, transferring information from one domain to another, and addressing theoretical issues on improving the privacy and incentive… factors of federated learning as w.
Sprache: Englisch
Verlag: Springer, Berlin|Springer International Publishing|Springer, 2022
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Gebunden. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book provides a collection of recent research works on learning from decentralized data, transferring information from one domain to another, and addressing theoretical issues on improving the privacy and… incentive factors of federated learning as w.
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Buch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides a collection of recent research works on learning from decentralized data, transferring information from one domain to another, and addressing theoretical issues on improving the privacy and incentive factors of federated lear…ning as well as its connection with transfer learning and reinforcement learning. Over the last few years, the machine learning community has become fascinated by federated and transfer learning. Transfer and federated learning have achieved great success and popularity in many different fields of application. The intended audience of this book is students and academics aiming to apply federated and transfer learning to solve different kinds of real-world problems, as well as scientists, researchers, and practitioners in AI industries, autonomous vehicles, and cyber-physical systems who wish to pursue new scientific innovations and update their knowledge on federated and transfer learning and their applications.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 380 pp. Englisch.
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides a collection of recent research works on learning from decentralized data, transferring information from one domain to another, and addressing theoretical issues on improving the privacy and incentive factors of federat…ed learning as well as its connection with transfer learning and reinforcement learning. Over the last few years, the machine learning community has become fascinated by federated and transfer learning. Transfer and federated learning have achieved great success and popularity in many different fields of application. The intended audience of this book is students and academics aiming to apply federated and transfer learning to solve different kinds of real-world problems, as well as scientists, researchers, and practitioners in AI industries, autonomous vehicles, and cyber-physical systems who wish to pursue new scientific innovations and update their knowledge on federated and transfer learning and their applications.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 380 pp. Englisch.
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