Information theory, inference, and learning algorithms:
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Cambridge [u.a.]
Cambridge Univ. Press
2010
|
| Edition: | 9. printing |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Item Description: | Hier auch später erschienene, unveränderte Nachdrucke |
| Physical Description: | XII, 628 S. Ill., graph. Darst. |
| ISBN: | 9780521642989 |
Staff View
MARC
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| 100 | 1 | |a MacKay, David J. C. |d 1967-2016 |e Verfasser |0 (DE-588)173311342 |4 aut | |
| 245 | 1 | 0 | |a Information theory, inference, and learning algorithms |c David J. C. MacKay |
| 250 | |a 9. printing | ||
| 264 | 1 | |a Cambridge [u.a.] |b Cambridge Univ. Press |c 2010 | |
| 300 | |a XII, 628 S. |b Ill., graph. Darst. | ||
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Record in the Search Index
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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
Boltzmaiin 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
Convolut
ional Codes and Turbo Codes
. 574
49
Repeat- Accumulate Codes
. 582
50
Digital Fountain Codes
. 589
VII
Appendices
. 597
A Notation
. 598
В
Some Physics
. 601
С
Some Mathematics
. 605
Bibliography
. 613
Index
. 620 |
| any_adam_object | 1 |
| author | MacKay, David J. C. 1967-2016 |
| author_GND | (DE-588)173311342 |
| author_facet | MacKay, David J. C. 1967-2016 |
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| discipline | Allgemeines Informatik |
| edition | 9. printing |
| format | Book |
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| id | DE-604.BV036858214 |
| illustrated | Illustrated |
| indexdate | 2024-07-20T05:16:02Z |
| institution | BVB |
| isbn | 9780521642989 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-020774035 |
| oclc_num | 650811697 |
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| physical | XII, 628 S. Ill., graph. Darst. |
| publishDate | 2010 |
| publishDateSearch | 2010 |
| publishDateSort | 2010 |
| publisher | Cambridge Univ. Press |
| record_format | marc |
| spelling | MacKay, David J. C. 1967-2016 Verfasser (DE-588)173311342 aut Information theory, inference, and learning algorithms David J. C. MacKay 9. printing Cambridge [u.a.] Cambridge Univ. Press 2010 XII, 628 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Hier auch später erschienene, unveränderte Nachdrucke Informationstheorie (DE-588)4026927-9 gnd rswk-swf Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf Inferenz Künstliche Intelligenz (DE-588)4333533-0 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 Digitalisierung UB Bayreuth application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020774035&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 (DE-588)4026927-9 gnd Maschinelles Lernen (DE-588)4193754-5 gnd Inferenz Künstliche Intelligenz (DE-588)4333533-0 gnd |
| subject_GND | (DE-588)4026927-9 (DE-588)4193754-5 (DE-588)4333533-0 |
| 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 (DE-588)4026927-9 gnd Maschinelles Lernen (DE-588)4193754-5 gnd Inferenz Künstliche Intelligenz (DE-588)4333533-0 gnd |
| topic_facet | Informationstheorie Maschinelles Lernen Inferenz Künstliche Intelligenz |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020774035&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT mackaydavidjc informationtheoryinferenceandlearningalgorithms |