Springer Series in the Data Sciences – serie
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22 produkter
Cohesive Subgraph Computation over Large Sparse Graphs
Algorithms, Data Structures, and Programming Techniques
Av Lijun Chang, Lu Qin
Inbunden, 2019
568 kr
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This book is considered the first extended survey on algorithms and techniques for efficient cohesive subgraph computation. With rapid development of information technology, huge volumes of graph data are accumulated. An availability of rich graph data not only brings great opportunities for …
Parametric Approach to Nonparametric Statistics
Av Mayer Alvo, Philip L. H. Yu
Häftad, 2018
552 kr
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This book demonstrates that nonparametric statistics can be taught from a parametric point of view. As a result, one can exploit various parametric tools such as the use of the likelihood function, penalized likelihood and score functions to not only derive well-known tests but to also go beyond …
Deep Learning Architectures
A Mathematical Approach
Av Ovidiu Calin
Inbunden, 2020
1129 kr
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This book describes how neural networks operate from the mathematical point of view. As a result, neural networks can be interpreted both as function universal approximators and information processors. The book bridges the gap between ideas and concepts of neural networks, which are used nowadays …
Deep Learning Architectures
A Mathematical Approach
Av Ovidiu Calin
Häftad, 2021
442 kr
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This book describes how neural networks operate from the mathematical point of view. As a result, neural networks can be interpreted both as function universal approximators and information processors. The book bridges the gap between ideas and concepts of neural networks, which are used nowadays …
First-order and Stochastic Optimization Methods for Machine Learning
Av Guanghui Lan
Inbunden, 2020
944 kr
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This book covers not only foundational materials but also the most recent progresses made during the past few years on the area of machine learning algorithms. In spite of the intensive research and development in this area, there does not exist a systematic treatment to introduce the fundamental …
First-order and Stochastic Optimization Methods for Machine Learning
Av Guanghui Lan
Häftad, 2021
923 kr
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This book covers not only foundational materials but also the most recent progresses made during the past few years on the area of machine learning algorithms. In spite of the intensive research and development in this area, there does not exist a systematic treatment to introduce the fundamental …
Mathematical Foundations for Data Analysis
Inbunden, 2021
660 kr
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This textbook, suitable for an early undergraduate up to a graduate course, provides an overview of many basic principles and techniques needed for modern data analysis. In particular, this book was designed and written as preparation for students planning to take rigorous Machine Learning and Data …
Mathematical Foundations for Data Analysis
Häftad, 2022
660 kr
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This textbook, suitable for an early undergraduate up to a graduate course, provides an overview of many basic principles and techniques needed for modern data analysis. In particular, this book was designed and written as preparation for students planning to take rigorous Machine Learning and Data …
Statistics with Julia
Fundamentals for Data Science, Machine Learning and Artificial Intelligence
Av Yoni Nazarathy, Hayden Klok
Inbunden, 2021
1967 kr
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This monograph uses the Julia language to guide the reader through an exploration of the fundamental concepts of probability and statistics, all with a view of mastering machine learning, data science, and artificial intelligence. The text does not require any prior statistical knowledge and only …
Statistics with Julia
Fundamentals for Data Science, Machine Learning and Artificial Intelligence
Av Yoni Nazarathy, Hayden Klok
Häftad, 2022
1967 kr
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This monograph uses the Julia language to guide the reader through an exploration of the fundamental concepts of probability and statistics, all with a view of mastering machine learning, data science, and artificial intelligence. The text does not require any prior statistical knowledge and only …
Data Science for Public Policy
Av Jeffrey C. Chen, Edward A. Rubin m. fl.
Inbunden, 2021
715 kr
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This textbook presents the essential tools and core concepts of data science to public officials, policy analysts, and economists among others in order to further their application in the public sector. An expansion of the quantitative economics frameworks presented in policy and business schools, …
Data Science for Public Policy
Av Jeffrey C. Chen, Edward A. Rubin m. fl.
Häftad, 2022
552 kr
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This textbook presents the essential tools and core concepts of data science to public officials, policy analysts, and economists among others in order to further their application in the public sector. An expansion of the quantitative economics frameworks presented in policy and business schools, …
Statistics in the Public Interest
In Memory of Stephen E. Fienberg
Av Alicia L. Carriquiry, Judith M. Tanur m. fl.
Inbunden, 2022
1423 kr
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This edited volume surveys a variety of topics in statistics and the social sciences in memory of the late Stephen Fienberg. The book collects submissions from a wide range of contemporary authors to explore the fields in which Fienberg made significant contributions, including contingency tables …
Statistics in the Public Interest
In Memory of Stephen E. Fienberg
Av Alicia L. Carriquiry, Judith M. Tanur m. fl.
Häftad, 2023
1423 kr
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This edited volume surveys a variety of topics in statistics and the social sciences in memory of the late Stephen Fienberg. The book collects submissions from a wide range of contemporary authors to explore the fields in which Fienberg made significant contributions, including contingency tables …
Multivariate Data Analysis on Matrix Manifolds
(with Manopt)
Av Nickolay Trendafilov, Michele Gallo
Inbunden, 2021
420 kr
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This graduate-level textbook aims to give a unified presentation and solution of several commonly used techniques for multivariate data analysis (MDA). Unlike similar texts, it treats the MDA problems as optimization problems on matrix manifolds defined by the MDA model parameters, allowing them to …
Multivariate Data Analysis on Matrix Manifolds
(with Manopt)
Av Nickolay Trendafilov, Michele Gallo
Häftad, 2022
552 kr
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This graduate-level textbook aims to give a unified presentation and solution of several commonly used techniques for multivariate data analysis (MDA). Unlike similar texts, it treats the MDA problems as optimization problems on matrix manifolds defined by the MDA model parameters, allowing them to …
Statistical Inference and Machine Learning for Big Data
Av Mayer Alvo
Inbunden, 2022
1532 kr
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This book presents a variety of advanced statistical methods at a level suitable for advanced undergraduate and graduate students as well as for others interested in familiarizing themselves with these important subjects. It proceeds to illustrate these methods in the context of real-life …
Statistical Inference and Machine Learning for Big Data
Av Mayer Alvo
Häftad, 2023
1532 kr
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This book presents a variety of advanced statistical methods at a level suitable for advanced undergraduate and graduate students as well as for others interested in familiarizing themselves with these important subjects. It proceeds to illustrate these methods in the context of real-life …
Foundations of Federated Learning
Inbunden, 2026
875 kr
Kommande
This book provides a rigorous yet accessible introduction to federated learning as a privacy-aware, decentralized, and trustworthy approach to artificial intelligence. As data becomes increasingly distributed across devices, organizations, institutions, and jurisdictions, conventional centralized …
Lectures on the Nearest Neighbor Method
Inbunden, 2015
1532 kr
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This text presents a wide-ranging and rigorous overview of nearest neighbor methods, one of the most important paradigms in machine learning. Now in one self-contained volume, this book systematically covers key statistical, probabilistic, combinatorial and geometric ideas for understanding, …
Lectures on the Nearest Neighbor Method
Häftad, 2019
1532 kr
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This text presents a wide-ranging and rigorous overview of nearest neighbor methods, one of the most important paradigms in machine learning. Now in one self-contained volume, this book systematically covers key statistical, probabilistic, combinatorial and geometric ideas for understanding, …
Parametric Approach to Nonparametric Statistics
Av Mayer Alvo, Philip L. H. Yu
Inbunden, 2018
769 kr
Lägg i varukorg
This book demonstrates that nonparametric statistics can be taught from a parametric point of view. As a result, one can exploit various parametric tools such as the use of the likelihood function, penalized likelihood and score functions to not only derive well-known tests but to also go beyond …
