Coverart for item
The Resource Foundations of machine learning, Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar

Foundations of machine learning, Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar

Label
Foundations of machine learning
Title
Foundations of machine learning
Statement of responsibility
Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar
Creator
Contributor
Subject
Genre
Language
eng
Member of
Cataloging source
N$T
Dewey number
006.3/1
Illustrations
illustrations
Index
index present
LC call number
Q325.5
LC item number
.M64 2012eb
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
Series statement
Adaptive computation and machine learning
Label
Foundations of machine learning, Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar
Link
http://web.ebscohost.com/ehost/detail?vid=3&hid=25&sid=905694d7-09f8-4045-aa7b-209a66fc18bb%40sessionmgr10&bdata=JnNpdGU9ZWhvc3QtbGl2ZQ==#db=nlebk&AN=478737
Instantiates
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • ""Contents""; ""Preface""; ""1 Introduction""; ""1.1 Applications and problems""; ""1.2 Definitions and terminology""; ""1.3 Cross-validation""; ""1.4 Learning scenarios""; ""1.5 Outline""; ""2 The PAC Learning Framework""; ""2.1 The PAC learning model""; ""2.2 Guarantees for finite hypothesis setsâ€?consistent case""; ""2.3 Guarantees for finite hypothesis setsâ€?inconsistent case""; ""2.4 Generalities""; ""2.5 Chapter notes""; ""2.6 Exercises""; ""3 Rademacher Complexity and VC Dimension""; ""3.1 Rademacher complexity""; ""3.2 Growth function""; ""3.3 VC-dimension""; ""3.4 Lower bounds""
  • ""3.5 Chapter notes""""3.6 Exercises""; ""4 Support Vector Machines""; ""4.1 Linear classification""; ""4.2 SVMsâ€?separable case""; ""4.3 SVMsâ€?non-separable case""; ""4.4 Margin theory""; ""4.5 Chapter notes""; ""4.6 Exercises""; ""5 Kernel Methods""; ""5.1 Introduction""; ""5.2 Positive definite symmetric kernels""; ""5.3 Kernel-based algorithms""; ""5.4 Negative definite symmetric kernels""; ""5.5 Sequence kernelsThe examples given in the previous""; ""5.6 Chapter notes""; ""5.7 Exercises""; ""6 Boosting""; ""6.1 Introduction""; ""6.2 AdaBoost""; ""6.3 Theoretical results""
  • ""6.4 Discussion""""6.5 Chapter notes""; ""6.6 Exercises""; ""7 On-Line Learning""; ""7.1 Introduction""; ""7.2 Prediction with expert advice""; ""7.3 Linear classification""; ""7.4 On-line to batch conversion""; ""7.5 Game-theoretic connection""; ""7.6 Chapter notes""; ""7.7 Exercises""; ""8 Multi-Class Classification""; ""8.1 Multi-class classification problem""; ""8.2 Generalization bounds""; ""8.3 Uncombined multi-class algorithms""; ""8.4 Aggregated multi-class algorithms""; ""8.5 Structured prediction algorithms""; ""8.6 Chapter notes""; ""8.7 Exercises""; ""9 Ranking""
  • ""9.1 The problem of ranking""""9.2 Generalization bound""; ""9.3 Ranking with SVMs""; ""9.4 RankBoost""; ""9.5 Bipartite ranking""; ""9.6 Preference-based setting""; ""9.7 Discussion""; ""9.8 Chapter notes""; ""9.9 Exercises""; ""10 Regression""; ""10.1 The problem of regression""; ""10.2 Generalization bounds""; ""10.3 Regression algorithms""; ""10.4 Chapter notes""; ""10.5 Exercises""; ""11 Algorithmic Stability""; ""11.1 Definitions""; ""11.2 Stability-based generalization guarantee""; ""11.3 Stability of kernel-based regularization algorithms""; ""11.4 Chapter notes""; ""11.5 Exercises""
  • ""12 Dimensionality Reduction""""12.1 Principal Component Analysis""; ""12.2 Kernel Principal Component Analysis (KPCA)""; ""12.3 KPCA and manifold learning""; ""12.4 Johnson-Lindenstrauss lemma""; ""12.5 Chapter notes""; ""12.6 Exercises""; ""13 Learning Automata and Languages""; ""13.1 Introduction""; ""13.2 Finite automata""; ""13.3 Efficient exact learning""; ""13.4 Identification in the limit""; ""13.5 Chapter notes""; ""13.6 Exercises""; ""14 Reinforcement Learning""; ""14.1 Learning scenario""; ""14.2 Markov decision process model""; ""14.3 Policy""; ""14.4 Planning algorithms""
Control code
ocn809846149
Dimensions
unknown
Extent
1 online resource (xii, 414 pages)
File format
unknown
Form of item
online
Isbn
9780262305662
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other physical details
illustrations.
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
Stock number
22573/ctt58f16d
System control number
(OCoLC)809846149
Label
Foundations of machine learning, Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar
Link
http://web.ebscohost.com/ehost/detail?vid=3&hid=25&sid=905694d7-09f8-4045-aa7b-209a66fc18bb%40sessionmgr10&bdata=JnNpdGU9ZWhvc3QtbGl2ZQ==#db=nlebk&AN=478737
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • ""Contents""; ""Preface""; ""1 Introduction""; ""1.1 Applications and problems""; ""1.2 Definitions and terminology""; ""1.3 Cross-validation""; ""1.4 Learning scenarios""; ""1.5 Outline""; ""2 The PAC Learning Framework""; ""2.1 The PAC learning model""; ""2.2 Guarantees for finite hypothesis setsâ€?consistent case""; ""2.3 Guarantees for finite hypothesis setsâ€?inconsistent case""; ""2.4 Generalities""; ""2.5 Chapter notes""; ""2.6 Exercises""; ""3 Rademacher Complexity and VC Dimension""; ""3.1 Rademacher complexity""; ""3.2 Growth function""; ""3.3 VC-dimension""; ""3.4 Lower bounds""
  • ""3.5 Chapter notes""""3.6 Exercises""; ""4 Support Vector Machines""; ""4.1 Linear classification""; ""4.2 SVMsâ€?separable case""; ""4.3 SVMsâ€?non-separable case""; ""4.4 Margin theory""; ""4.5 Chapter notes""; ""4.6 Exercises""; ""5 Kernel Methods""; ""5.1 Introduction""; ""5.2 Positive definite symmetric kernels""; ""5.3 Kernel-based algorithms""; ""5.4 Negative definite symmetric kernels""; ""5.5 Sequence kernelsThe examples given in the previous""; ""5.6 Chapter notes""; ""5.7 Exercises""; ""6 Boosting""; ""6.1 Introduction""; ""6.2 AdaBoost""; ""6.3 Theoretical results""
  • ""6.4 Discussion""""6.5 Chapter notes""; ""6.6 Exercises""; ""7 On-Line Learning""; ""7.1 Introduction""; ""7.2 Prediction with expert advice""; ""7.3 Linear classification""; ""7.4 On-line to batch conversion""; ""7.5 Game-theoretic connection""; ""7.6 Chapter notes""; ""7.7 Exercises""; ""8 Multi-Class Classification""; ""8.1 Multi-class classification problem""; ""8.2 Generalization bounds""; ""8.3 Uncombined multi-class algorithms""; ""8.4 Aggregated multi-class algorithms""; ""8.5 Structured prediction algorithms""; ""8.6 Chapter notes""; ""8.7 Exercises""; ""9 Ranking""
  • ""9.1 The problem of ranking""""9.2 Generalization bound""; ""9.3 Ranking with SVMs""; ""9.4 RankBoost""; ""9.5 Bipartite ranking""; ""9.6 Preference-based setting""; ""9.7 Discussion""; ""9.8 Chapter notes""; ""9.9 Exercises""; ""10 Regression""; ""10.1 The problem of regression""; ""10.2 Generalization bounds""; ""10.3 Regression algorithms""; ""10.4 Chapter notes""; ""10.5 Exercises""; ""11 Algorithmic Stability""; ""11.1 Definitions""; ""11.2 Stability-based generalization guarantee""; ""11.3 Stability of kernel-based regularization algorithms""; ""11.4 Chapter notes""; ""11.5 Exercises""
  • ""12 Dimensionality Reduction""""12.1 Principal Component Analysis""; ""12.2 Kernel Principal Component Analysis (KPCA)""; ""12.3 KPCA and manifold learning""; ""12.4 Johnson-Lindenstrauss lemma""; ""12.5 Chapter notes""; ""12.6 Exercises""; ""13 Learning Automata and Languages""; ""13.1 Introduction""; ""13.2 Finite automata""; ""13.3 Efficient exact learning""; ""13.4 Identification in the limit""; ""13.5 Chapter notes""; ""13.6 Exercises""; ""14 Reinforcement Learning""; ""14.1 Learning scenario""; ""14.2 Markov decision process model""; ""14.3 Policy""; ""14.4 Planning algorithms""
Control code
ocn809846149
Dimensions
unknown
Extent
1 online resource (xii, 414 pages)
File format
unknown
Form of item
online
Isbn
9780262305662
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other physical details
illustrations.
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
Stock number
22573/ctt58f16d
System control number
(OCoLC)809846149

Library Locations

    • Waubonsee: Sugar Grove Campus - Todd LibraryBorrow it
      Collins Hall 2nd Floor Waubonsee Community College Route 47 at Waubonsee Drive, Sugar Grove, IL, 60554-9454, US
      41.7974 -88.45785
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