Meta-algorithmics: patterns for robust, low-cost, high-quality systems
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Chichester
Wiley
2013
|
| Schlagworte: | |
| Online-Zugang: | Cover image Inhaltsverzeichnis |
| Beschreibung: | "The intent is to highlight the salient differences in multiple approaches to useful solutions in each of these arenas"-- Provided by publisher. |
| Beschreibung: | XII, 374 S. |
| ISBN: | 9781118343364 |
Internformat
MARC
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| 100 | 1 | |a Simske, Steven J. |e Verfasser |0 (DE-588)1038037042 |4 aut | |
| 245 | 1 | 0 | |a Meta-algorithmics |b patterns for robust, low-cost, high-quality systems |c Steven J. Simske |
| 264 | 1 | |a Chichester |b Wiley |c 2013 | |
| 300 | |a XII, 374 S. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 500 | |a "The intent is to highlight the salient differences in multiple approaches to useful solutions in each of these arenas"-- Provided by publisher. | ||
| 650 | 4 | |a Computer algorithms | |
| 650 | 4 | |a Parallel algorithms | |
| 650 | 4 | |a Heuristic programming | |
| 650 | 4 | |a Computer systems |x Costs | |
| 650 | 4 | |a Computer systems |x Quality control | |
| 650 | 7 | |a TECHNOLOGY & ENGINEERING / Imaging Systems |2 bisacsh | |
| 650 | 0 | 7 | |a Computer |0 (DE-588)4070083-5 |2 gnd |9 rswk-swf |
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Datensatz im Suchindex
| _version_ | 1804150550779920384 |
|---|---|
| adam_text | Contents
Acknowledgments
xi
1
Introduction and Overview
1
1.
1 Introduction
1
.2
Why Is This Book Important?
2
.3
Organization of the Book
3
.4
Informatics
4
.5
Ensemble Learning
6
.6
Machine Learning/Intelligence
7
1.6.1
Regression and Entropy
8
1.6.2
SVM
s
and Kernels
9
1.6.3
Probability
15
1.6.4
U
^supervised Learning
17
1.6.5
Dimensionality Reduction
18
1.6.6
Optimization and Search
20
1.7
Artificial Intelligence
22
1.7.1
Neural Networks
22
1.7.2
Genetic Algorithms
25
1.7.3
Markov Models
28
1.8
Data Mining/Knowledge Discovery
31
1.9
Classification
32
1.10
Recognition
38
1.11
System-Based Analysis
39
1.12
Summary
39
References
40
2
Parallel Forms of Parallelism
42
2.1
Introduction
42
2.2
Parallelism by Task
43
2.2.1
Definition
43
2.2.2
Application to Algorithms and Architectures
46
2.2.3
Application to Scheduling
51
2.3
Parallelism by Component
52
2.3.
1 Definition and Extension to Parallel-Conditional Processing
52
vi
Contents
2.3.2
Application
to Data
Mining,
Search, and Other Algorithms
55
2.3.3
Application to Software Development
59
2.4
Parallelism by Meta-algorithm
64
2.4.1
Meta-algorithmics and Algorithms
66
2.4.2
Meta-algorithmics and Systems
67
2.4.3
Meta-algorithmics and Parallel Processing
68
2.4.4
Meta-algorithmics and Data Collection
69
2.4.5
Meta-algorithmics and Software Development
70
2.5
Summary
71
References
72
3
Domain Areas: Where Are These Relevant?
73
3.1
Introduction
73
3.2
Overview of the Domains
74
3.3
Primary Domains
75
3.3.
1 Document Understanding
75
3.3.2
image Understanding
77
3.3.3
Biometrics
78
3.3.4
Security Printing
79
3.4
Secondary Domains
86
3.4.
1 Image Segmentation
86
3.4.2
Speech Recognition
90
3.4.3
Medical Signal Processing
90
3.4.4
Medical Imaging
92
3.4.5
Natural Language Processing
95
3.4.6
Surveillance
97
3.4.7
Optical Character Recognition
98
3.4.8
Security Analytics
101
3.5
Summary
101
References
102
4
Applications of Parallelism by Task
104
4.1
Introduction
104
4.2
Primary Domains
105
4.2.1
Document Understanding
112
4.2.2
Image Understanding
118
4.2.3
Biometrics
126
4.2.4
Security Printing
131
4.3
Summary
135
References
136
5
Application of Parallelism by Component
137
5.1
Introduction
137
5.2
Primary Domains
138
5.2.1
Document Understanding
138
5.2.2
Image Understanding
152
Contents
vii
5.2.3
Biometrics
162
5.2.4
Security Printing
170
5.3
Summary
172
References
173
6
Introduction to Meta-algorithmics
175
6.1
Introduction
175
6.2
First-Order Meta-algorithmics
178
6.2.
1
Séquentiel
I Try
7 8
6.2.2
Constrained Substitute
181
6.2.3
Voting and Weighted Voting
184
6.2.4
Predictive Selection
189
6.2.5
Tessellation and Recombination
192
6.3
Second-Order Meta-algorithmics
195
6.3.
1 Confusion Matrix and Weighted Confusion Matrix
195
6.3.2
Confusion Matrix with Output Space Transformation
(Probability Space Transformation)
199
6.3.3
Tessellation and Recombination with Expert
Decis
ione r
203
6.3.4
Predictive Selection with Secondary Engines
206
6.3.5
Single Engine with Required Precision
208
6.3.6
Majority Voting or Weighted Confusion Matrix
209
6.3.7
Majority Voting or Best Engine
210
6.3.8
Best Engine with Differential Confidence or Second Best Engine
212
6.3.9
Best Engine with Absolute Confidence or Weighted
Confusion Matrix
217
6.4
Third-Order Meta-algorithmics
218
6.4.1
Feedback
219
6.4.2
Proof by Task Completion
221
6.4.3
Confusion Matrix for Feedback
224
6.4.4
Expert Feedback
228
6.4.5
Sensitivity Analysis
232
6.4.6
Regional Optimization (Extended Predictive Selection)
236
6.4.7
Generalized Hybridization
239
6.5
Summary
240
References
240
7
First-Order Meta-algorithmics and Their Applications
241
7.1
Introduction
241
7.2
First-Order Meta-algorithmics and the Black Box
241
7.3
Primary Domains
242
7.3.1
Document Understanding
242
7.3.2
¡mage Understanding
246
7.3.3
Biometrics
252
7.3.4
Security Printing
256
7.4
Secondary Domains
257
7.4.1
Medical Signal Processing
258
viii Contents
7.4.2
Medical
Imaging
264
7.4.3
Natural
Language
Processing
268
7.5
Summary
271
References
271
8
Second-Order Meta-algorithmics and Their Applications
272
8.1
Introduction
272
8.2
Second-Order Meta-algorithmics and Targeting the Fringes
273
8.3
Primary Domains
279
8.3.1
Document Understanding
280
8.3.2
Image Understanding
293
8.3.3
Biometrics
297
8.3.4
Security Printing
299
8.4
Secondary Domains
304
8.4.
J
Image Segmentation
305
8.4.2
Speech Recognition
307
8.5
Summary
308
References
308
9
Third-Order Meta-algorithmics and Their Applications
310
9.1
Introduction
310
9.2
Third-Order Meta-algorithmic Patterns
31 1
9.2.1
Examples Covered
311
9.2.2
Training-Gap-Targeted Feedback
31
I
9.3
Primary Domains
313
9.3.1
Document Understanding
313
9.3.2
Image Understanding
315
9.3.3
Biometrics
318
9.3.4
Security Printing
323
9.4
Secondary Domains
328
9.4.1
Surveillance
328
9.4.2
Optical Character Recognition
334
9.4.3
Security Analytics
337
9.5
Summary
340
References
341
10
Building More Robust Systems
342
10.1
Introduction
342
10.2
Summarization
342
J
0.2.
J
Ground Truthing for Meta-algorithmics
342
10.2.2
Meta-algorithmics for Keyword Generation
347
10.3
Cloud Systems
350
10.4
Mobile Systems
353
10.5
Scheduling
355
10.6
Classification
356
10.7
Summary
358
Reference
359
Contents ¡x
360
360
362
365
367
368
368
Index 369
11
The
Future
11.1
Recapitulation
11.2
The Pattern of All Patience
11.3
Beyond the Pale
11.4
Coming Soon
11.5
Summary
References
|
| any_adam_object | 1 |
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| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Book |
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| indexdate | 2024-07-10T00:40:43Z |
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| isbn | 9781118343364 |
| language | English |
| lccn | 2013004488 |
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| spelling | Simske, Steven J. Verfasser (DE-588)1038037042 aut Meta-algorithmics patterns for robust, low-cost, high-quality systems Steven J. Simske Chichester Wiley 2013 XII, 374 S. txt rdacontent n rdamedia nc rdacarrier "The intent is to highlight the salient differences in multiple approaches to useful solutions in each of these arenas"-- Provided by publisher. Computer algorithms Parallel algorithms Heuristic programming Computer systems Costs Computer systems Quality control TECHNOLOGY & ENGINEERING / Imaging Systems bisacsh Computer (DE-588)4070083-5 gnd rswk-swf Algorithmus (DE-588)4001183-5 gnd rswk-swf Computer (DE-588)4070083-5 s Algorithmus (DE-588)4001183-5 s DE-604 http://catalogimages.wiley.com/images/db/jimages/9781118343364.jpg Cover image Digitalisierung UB Bamberg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026124986&sequence=000004&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Simske, Steven J. Meta-algorithmics patterns for robust, low-cost, high-quality systems Computer algorithms Parallel algorithms Heuristic programming Computer systems Costs Computer systems Quality control TECHNOLOGY & ENGINEERING / Imaging Systems bisacsh Computer (DE-588)4070083-5 gnd Algorithmus (DE-588)4001183-5 gnd |
| subject_GND | (DE-588)4070083-5 (DE-588)4001183-5 |
| title | Meta-algorithmics patterns for robust, low-cost, high-quality systems |
| title_auth | Meta-algorithmics patterns for robust, low-cost, high-quality systems |
| title_exact_search | Meta-algorithmics patterns for robust, low-cost, high-quality systems |
| title_full | Meta-algorithmics patterns for robust, low-cost, high-quality systems Steven J. Simske |
| title_fullStr | Meta-algorithmics patterns for robust, low-cost, high-quality systems Steven J. Simske |
| title_full_unstemmed | Meta-algorithmics patterns for robust, low-cost, high-quality systems Steven J. Simske |
| title_short | Meta-algorithmics |
| title_sort | meta algorithmics patterns for robust low cost high quality systems |
| title_sub | patterns for robust, low-cost, high-quality systems |
| topic | Computer algorithms Parallel algorithms Heuristic programming Computer systems Costs Computer systems Quality control TECHNOLOGY & ENGINEERING / Imaging Systems bisacsh Computer (DE-588)4070083-5 gnd Algorithmus (DE-588)4001183-5 gnd |
| topic_facet | Computer algorithms Parallel algorithms Heuristic programming Computer systems Costs Computer systems Quality control TECHNOLOGY & ENGINEERING / Imaging Systems Computer Algorithmus |
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