Information theory, inference, and learning algorithms:
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Cambridge [u.a.]
Cambridge Univ. Press
2009
|
| Edition: | 8. print. |
| Subjects: | |
| Online Access: | Volltext Inhaltsverzeichnis |
| Item Description: | Includes bibliographical references and index |
| Physical Description: | XII, 628 S. Ill., graph. Darst. |
| ISBN: | 9780521642989 |
Staff View
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Record in the Search Index
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| adam_text | Titel: Information theory, inference, and learning algorithms
Autor: MacKay, David J. C.
Jahr: 2009
Contents
Preface v
1 Introduction to Information Theory 3
2 Probability, Entropy, and Inference 22
3 More about Inference 48
I Data Compression 65
4 The Source Coding Theorem 67
5 Symbol Codes 91
6 Stream Codes 110
7 Codes for Integers 132
II Noisy-Channel Coding 137
8 Dependent Random Variables 138
9 Communication over a Noisy Channel 146
10 The Noisy-Channel Coding Theorem 162
11 Error-Correcting Codes and Real Channels 177
III Further Topics in Information Theory 191
12 Hash Codes: Codes for Efficient Information Retrieval . . 193
13 Binary Codes 206
14 Very Good Linear Codes Exist 229
15 Further Exercises on Information Theory 233
16 Message Passing 241
17 Communication over Constrained Noiseless Channels . . . 248
18 Crosswords and Codebreaking 260
19 Why have Sex? Information Acquisition and Evolution . . 269
IV Probabilities and Inference 281
20 An Example Inference Task: Clustering 284
21 Exact Inference by Complete Enumeration 293
22 Maximum Likelihood and Clustering 300
23 Useful Probability Distributions 311
24 Exact Marginalization 319
25 Exact Marginalization in Trellises 324
26 Exact Marginalization in Graphs 334
27 Laplace s Method 341
28 Model Comparison and Occam s Razor 343
29 Monte Carlo Methods 357
30 Efficient Monte Carlo Methods 387
31 Ising Models 400
32 Exact Monte Carlo Sampling 413
33 Variational Methods 422
34 Independent Component Analysis and Latent Variable Mod¬
elling 437
35 Random Inference Topics 445
36 Decision Theory 451
37 Bayesian Inference and Sampling Theory 457
V Neural networks 467
38 Introduction to Neural Networks 468
39 The Single Neuron as a Classifier 471
40 Capacity of a Single Neuron 483
41 Learning as Inference 492
42 Hopfield Networks 505
43 Boltzmann Machines 522
44 Supervised Learning in Multilayer Networks 527
45 Gaussian Processes 535
46 Deconvolution 549
VI Sparse Graph Codes 555
47 Low-Density Parity-Check Codes 557
48 Convolutional Codes and Turbo Codes 574
49 Repeat-Accumulate Codes 582
50 Digital Fountain Codes 589
VII Appendices 597
A Notation 598
B Some Physics 601
C Some Mathematics 605
Bibliography 613
Index 620
|
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| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 003 - Systems |
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| dewey-tens | 000 - Computer science, information, general works |
| discipline | Allgemeines Informatik |
| edition | 8. print. |
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| indexdate | 2024-07-09T22:04:20Z |
| institution | BVB |
| isbn | 9780521642989 |
| language | English |
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| physical | XII, 628 S. Ill., graph. Darst. |
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| spelling | MacKay, David J. C. 1967-2016 Verfasser (DE-588)173311342 aut Information theory, inference, and learning algorithms David J. C. MacKay 8. print. Cambridge [u.a.] Cambridge Univ. Press 2009 XII, 628 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Includes bibliographical references and index Informationstheorie - Maschinelles Lernen - Inferenz <Künstliche Intelligenz> Informationstheorie (DE-588)4026927-9 gnd rswk-swf Inferenz Künstliche Intelligenz (DE-588)4333533-0 gnd rswk-swf Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf Informationstheorie (DE-588)4026927-9 s Inferenz Künstliche Intelligenz (DE-588)4333533-0 s Maschinelles Lernen (DE-588)4193754-5 s DE-604 http://www.inference.phy.cam.ac.uk/mackay/itila/book.html kostenfrei Volltext HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018637941&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | MacKay, David J. C. 1967-2016 Information theory, inference, and learning algorithms Informationstheorie - Maschinelles Lernen - Inferenz <Künstliche Intelligenz> Informationstheorie (DE-588)4026927-9 gnd Inferenz Künstliche Intelligenz (DE-588)4333533-0 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
| subject_GND | (DE-588)4026927-9 (DE-588)4333533-0 (DE-588)4193754-5 |
| title | Information theory, inference, and learning algorithms |
| title_auth | Information theory, inference, and learning algorithms |
| title_exact_search | Information theory, inference, and learning algorithms |
| title_full | Information theory, inference, and learning algorithms David J. C. MacKay |
| title_fullStr | Information theory, inference, and learning algorithms David J. C. MacKay |
| title_full_unstemmed | Information theory, inference, and learning algorithms David J. C. MacKay |
| title_short | Information theory, inference, and learning algorithms |
| title_sort | information theory inference and learning algorithms |
| topic | Informationstheorie - Maschinelles Lernen - Inferenz <Künstliche Intelligenz> Informationstheorie (DE-588)4026927-9 gnd Inferenz Künstliche Intelligenz (DE-588)4333533-0 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
| topic_facet | Informationstheorie - Maschinelles Lernen - Inferenz <Künstliche Intelligenz> Informationstheorie Inferenz Künstliche Intelligenz Maschinelles Lernen |
| url | http://www.inference.phy.cam.ac.uk/mackay/itila/book.html http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018637941&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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