首页Kernel Methods and Machine Learning
Kernel Methods and Machine Learning
需积分: 9 45 浏览量 更新于2023-05-23 评论 收藏 3.49MB PDF 举报
书名：《Kernel Methods and Machine Learning》 作者：S. Y. KUNG 单位：Princeton University, New Jersey
9781107024960book CUP/KUN-L1 November 9, 2013 17:09 Page-i
Kernel Methods and Machine Learning
Offering a fundamental basis in kernel-based learning theory, this book covers both
statistical and algebraic principles. It provides over 30 major theorems for kernel-based
supervised and unsupervised learning models. The ﬁrst of the theorems establishes a
condition, arguably necessary and sufﬁcient, for the kernelization of learning models.
In addition, several other theorems are devoted to proving mathematical equivalence
between seemingly unrelated models.
With over 25 closed-form and iterative algorithms, the book provides a step-by-step
guide to algorithmic procedures and analyzing which factors to consider in tackling a
given problem, enabling readers to improve speciﬁcally designed learning algorithms
and build models for new applications or develop efﬁcient techniques suitable for green
machine learning technologies.
Numerous real-world examples and over 200 problems, several of which are
ATLAB-based simulation exercises, make this an essential resource for graduate stu-
dents in computer science, and in electrical and biomedical engineering. It is also
a useful reference for researchers and practitioners in the ﬁeld of machine learning.
Solutions to problems and additional resources are provided online for instructors.
S. Y. K
UNG is a Professor in the Department of Electrical Engineering at Princeton Uni-
versity. His research areas include VLSI array/parallel processors, system modeling
and identiﬁcation, wireless communication, statistical signal processing, multimedia
processing, sensor networks, bioinformatics, data mining, and machine learning.
9781107024960book CUP/KUN-L1 November 9, 2013 17:09 Page-ii
9781107024960book CUP/KUN-L1 November 9, 2013 17:09 Page-iii
Kernel Methods and
S. Y. KUNG
Princeton University, New Jersey
9781107024960book CUP/KUN-L1 November 9, 2013 17:09 Page-iv
University Printing House, Cambridge CB2 8BS, United Kingdom
Published in the United States of America by Cambridge University Press, New York
Cambridge University Press is part of the University of Cambridge.
It furthers the University’s mission by disseminating knowledge in the pursuit of
education, learning, and research at the highest international levels of excellence.
Information on this title: www.cambridge.org/9781107024960
Cambridge University Press 2014
This publication is in copyright. Subject to statutory exception
and to the provisions of relevant collective licensing agreements,
no reproduction of any part may take place without the written
permission of Cambridge University Press.
First published 2014
Printed and bound in the United Kingdom by the MPG Books Group
A catalogue record for this publication is available from the British Library
Library of Congress Cataloguing in Publication data
ISBN 978 1 107 702496 0 Hardback
Additional resources for this publication at www.cambridge.org/97811077024960
Cambridge University Press has no responsibility for the persistence or accuracy of
URLs for external or third-party internet websites referred to in this publication,
and does not guarantee that any content on such websites is, or will remain,
accurate or appropriate.
Write a paper about Deep-learning based analysis of metal-transfer images in GMAW process , requiring 10000 words
- 我的内容管理 收起
- 我的资源 快来上传第一个资源
- 我的收益 登录查看自己的收益
- 我的积分 登录查看自己的积分
- 我的C币 登录后查看C币余额