Gan Zhe Zeng Chan Jing Yan
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Gan Zhe Zeng Chan Jing Yan
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Author :
language : en
Publisher:
Release Date : 1957
Gan Zhe Zeng Chan Jing Yan written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1957 with categories.
Gan Zhe Zeng Chan Jing Yan
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Author : guang dong sheng nong ye ting Bian
language : en
Publisher:
Release Date :
Gan Zhe Zeng Chan Jing Yan written by guang dong sheng nong ye ting Bian and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Graph Representation Learning
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Author : William L. William L. Hamilton
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Graph Representation Learning written by William L. William L. Hamilton and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.
Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.
Water Margin
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Author : Nai'an Shi
language : en
Publisher:
Release Date : 1976
Water Margin written by Nai'an Shi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1976 with categories.
Chanting The Medicine Buddha Sutra
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Author : Criddle, Reed
language : en
Publisher: A-R Editions, Inc.
Release Date : 2020-01-01
Chanting The Medicine Buddha Sutra written by Criddle, Reed and has been published by A-R Editions, Inc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-01 with Music categories.
This edition, comprising a sound recording, transcription, and English translation, provides a record of the Liberation Rite of Water and Land as a resource for the study, analysis, and further exploration of both the Medicine Buddha Sutra and the accompanying liturgical service. The editor created it at the invitation of Fo Guang Shan monastery, and it outlines both the textual and musical elements of the service. Designed as a chantbook, it is intended to be a tool for all those who wish to participate in the vocal elements of the service, from the uninitiated monastery visitor to musical ensembles that might use these musical fragments as inspiration for appropriately staged performances. It is especially conceived for non-Chinese speaking monastics in the Buddhist college and/or those who have experience reading Western musical notation.
Federated Learning
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Author : Qiang Qiang Yang
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Federated Learning written by Qiang Qiang Yang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.
How is it possible to allow multiple data owners to collaboratively train and use a shared prediction model while keeping all the local training data private? Traditional machine learning approaches need to combine all data at one location, typically a data center, which may very well violate the laws on user privacy and data confidentiality. Today, many parts of the world demand that technology companies treat user data carefully according to user-privacy laws. The European Union's General Data Protection Regulation (GDPR) is a prime example. In this book, we describe how federated machine learning addresses this problem with novel solutions combining distributed machine learning, cryptography and security, and incentive mechanism design based on economic principles and game theory. We explain different types of privacy-preserving machine learning solutions and their technological backgrounds, and highlight some representative practical use cases. We show how federated learning can become the foundation of next-generation machine learning that caters to technological and societal needs for responsible AI development and application.
Artificial Intelligence In Asset Management
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Author : Söhnke M. Bartram
language : en
Publisher: CFA Institute Research Foundation
Release Date : 2020-08-28
Artificial Intelligence In Asset Management written by Söhnke M. Bartram and has been published by CFA Institute Research Foundation this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-28 with Business & Economics categories.
Artificial intelligence (AI) has grown in presence in asset management and has revolutionized the sector in many ways. It has improved portfolio management, trading, and risk management practices by increasing efficiency, accuracy, and compliance. In particular, AI techniques help construct portfolios based on more accurate risk and return forecasts and more complex constraints. Trading algorithms use AI to devise novel trading signals and execute trades with lower transaction costs. AI also improves risk modeling and forecasting by generating insights from new data sources. Finally, robo-advisors owe a large part of their success to AI techniques. Yet the use of AI can also create new risks and challenges, such as those resulting from model opacity, complexity, and reliance on data integrity.
The Case For Marriage
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Author : Linda Waite
language : en
Publisher: Crown
Release Date : 2002-03-05
The Case For Marriage written by Linda Waite and has been published by Crown this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-03-05 with Social Science categories.
A groundbreaking look at marriage, one of the most basic and universal of all human institutions, which reveals the emotional, physical, economic, and sexual benefits that marriage brings to individuals and society as a whole. The Case for Marriage is a critically important intervention in the national debate about the future of family. Based on the authoritative research of family sociologist Linda J. Waite, journalist Maggie Gallagher, and a number of other scholars, this book’s findings dramatically contradict the anti-marriage myths that have become the common sense of most Americans. Today a broad consensus holds that marriage is a bad deal for women, that divorce is better for children when parents are unhappy, and that marriage is essentially a private choice, not a public institution. Waite and Gallagher flatly contradict these assumptions, arguing instead that by a broad range of indices, marriage is actually better for you than being single or divorced– physically, materially, and spiritually. They contend that married people live longer, have better health, earn more money, accumulate more wealth, feel more fulfillment in their lives, enjoy more satisfying sexual relationships, and have happier and more successful children than those who remain single, cohabit, or get divorced. The Case for Marriage combines clearheaded analysis, penetrating cultural criticism, and practical advice for strengthening the institution of marriage, and provides clear, essential guidelines for reestablishing marriage as the foundation for a healthy and happy society. “A compelling defense of a sacred union. The Case for Marriage is well written and well argued, empirically rigorous and learned, practical and commonsensical.” -- William J. Bennett, author of The Book of Virtues “Makes the absolutely critical point that marriage has been misrepresented and misunderstood.” -- The Wall Street Journal www.broadwaybooks.com
An Inspiration To Give Rise To The Bodhi Mind
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Author : 實賢
language : en
Publisher:
Release Date : 2017-09
An Inspiration To Give Rise To The Bodhi Mind written by 實賢 and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09 with Bodhicitta (Buddhism) categories.
Representation Learning For Natural Language Processing
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Author : Zhiyuan Liu
language : en
Publisher: Springer Nature
Release Date : 2020-07-03
Representation Learning For Natural Language Processing written by Zhiyuan Liu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-03 with Computers categories.
This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.