Lifelong Machine Learning:
Gespeichert in:
| Beteiligte Personen: | , |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
San Rafael, California
Morgan & Claypool Publishers
[2017]
|
| Schriftenreihe: | Synthesis lectures on artificial intelligence and machine learning
33 |
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029400936&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Umfang: | XVII, 127 Seiten |
| ISBN: | 9781627055017 |
Internformat
MARC
| LEADER | 00000nam a2200000 cb4500 | ||
|---|---|---|---|
| 001 | BV043992760 | ||
| 003 | DE-604 | ||
| 005 | 20180914 | ||
| 007 | t| | ||
| 008 | 170111s2017 xx |||| 00||| eng d | ||
| 020 | |a 9781627055017 |9 978-1-62705-501-7 | ||
| 035 | |a (OCoLC)971362622 | ||
| 035 | |a (DE-599)BVBBV043992760 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-473 | ||
| 084 | |a ST 302 |0 (DE-625)143652: |2 rvk | ||
| 100 | 1 | |a Chen, Zhiyuan |e Verfasser |0 (DE-588)1123153329 |4 aut | |
| 245 | 1 | 0 | |a Lifelong Machine Learning |c Zhiyuan Chen, Google, Inc., Bing Liu, University of Illinois at Chicago |
| 264 | 1 | |a San Rafael, California |b Morgan & Claypool Publishers |c [2017] | |
| 300 | |a XVII, 127 Seiten | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 1 | |a Synthesis lectures on artificial intelligence and machine learning |v 33 | |
| 650 | 0 | 7 | |a Maschinelles Lernen |0 (DE-588)4193754-5 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Maschinelles Lernen |0 (DE-588)4193754-5 |D s |
| 689 | 0 | |5 DE-604 | |
| 700 | 1 | |a Liu, Bing |d 1963- |e Verfasser |0 (DE-588)1014900026 |4 aut | |
| 776 | 0 | 8 | |i Erscheint auch als |b Onlineausgabe |z 978-1-62705-877-3 |
| 830 | 0 | |a Synthesis lectures on artificial intelligence and machine learning |v 33 |w (DE-604)BV035750800 |9 33 | |
| 856 | 4 | 2 | |m Digitalisierung UB Bamberg - ADAM Catalogue Enrichment |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029400936&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-029400936 | |
Datensatz im Suchindex
| _version_ | 1819351063086497792 |
|---|---|
| adam_text | Contents
Preface......................................................... xv
Acknowledgments................................................... xvii
1 Introduction........................................................ 1
1.1 A Brief History of Lifelong Learning............................... .3
1.2 Definition of Lifelong Learning...................................5
1.3 Lifelong Learning System Architecture ............................8
1.4 Evaluation Methodology........................................... 10
1.5 Role of Big Data in Lifelong Learning.............................11
1.6 Outline of the Book...............................................11
2 Related Learning Paradigms......................................... 13
2.1 Transfer Learning.............................................. .13
2.1.1 Structural Correspondence Learning..........................14
2.1.2 Naive Bayes Transfer Classifier.............................. 14
2.1.3 Deep Learning in Transfer Learning ........................ 16
2.1.4 Difference from Lifelong Learning ..........................17
2.2 Multi-Task Learning ........................................ .17
2.2.1 Task Relatedness in Multi-Task Learning ..,.................18
2.2.2 GO-MTL: Multi-Task Learning using Latent Basis..............19
2.2.3 Deep Learning in Multi-Task Learning....................... 20
2.2.4 Difference from Lifelong Learning ..........................22
2.3 Online Learning.................................................. 23
2.3.1 Difference from Lifelong Learning............................23
2.4 Reinforcement Learning......................................... 24
2.4.1 Difference from Lifelong Learning ..........................24
2.5 Summary........................................................ .25
3 Lifelong Supervised Learning ............................................27
3.1 Definition and Overview....................................... 28
3.2 Lifelong Memory-based Learning................................... 29
Xll
3.2.1 Two Memory-based Learning Methods ............................29
3.2.2 Learning a New Representation for Lifelong Learning.............. 29
3.3 Lifelong Neural Networks.................................................30
3.3.1 MTL Net ..........................................................31
3.3.2 Lifelong EBNN ....................................................32
3.4 Cumulative Learning and Self-motivated Learning..........................33
3.4.1 Training a Cumulative Learning Model..............................34
3.4.2 Testing a Cumulative Learning Model ............................35
3.4.3 Open World Learning for Unseen Class Detection....................37
3.5 ELLA: An Efficient Lifelong Learning Algorithm ..........................39
3.5.1 Problem Setting...................................................40
3.5.2 Objective Function................................................40
3.5.3 Dealing with the First Inefficiency...............................41
3.5.4 Dealing with the Second Inefficiency..............................43
3.5.5 Active Task Selection.............................................44
3.6 I,SC: Lifelong Sentiment Classification..................................45
3.6.1 Naive Bayesian Text Classification................................45
3.6.2 Basic Ideas of LSC................................................47
3.6.3 LSC Technique.................................................... 48
3.7 Summary and Evaluation Datasets..........................................50
4 Lifelong Unsupervised Learning................................................53
4.1 Lifelong Topic Modeling..................................................53
4.2 LTM: A Lifelong Topic Model .............................................56
4.2.1 LTM Model.........................................................57
4.2.2 Topic Knowledge Mining............................................59
4.2.3 Incorporating Past Knowledge......................................60
4.2.4 Conditional Distribution of Gibbs Sampler.........................61
4.3 AMC: A Lifelong Topic Model for Small Data...............................62
4.3.1 Overall Algorithm of AMC..........................................62
4.3.2 Mining Must-link Knowledge........................................63
4.3.3 Mining Cannot-link Knowledge .....................................66
4.3.4 Extended Polya Urn Model........................................ 67
4.3.5 Sampling Distributions in Gibbs Sampler.......................... 69
4.4 Lifelong Information Extraction..........................................70
4.4.1 Lifelong Learning through Recommendation..........................72
4.4.2 AER Algorithm ....................................................72
xm
4.4.3 Knowledge Learning..............................................73
4.4.4 Recommendation using Past Knowledge............................74
4.5 Lifelong-RL: Lifelong Relaxation Labeling.............................76
4.5.1 Relaxation Labeling............................................ 76
4.5.2 Lifelong Relaxation Labeling................................... 77
4.6 Summary and Evaluation Datasets.......................................78
5 Lifelong Semi-supervised Learning for Information Extraction ................81
5.1 NELL: A Never Ending Language Learner................................ 82
5.2 NELL Architecture.................................................... 83
5.3 Extractors and Learning in NELL.......................................84
5.4 Coupling Constraints in NELL......................................... 87
5.5 Summary...............................................................87
6 Lifelong Reinforcement Learning..............................................89
6.1 Lifelong Reinforcement Learning through Multiple Environments ........90
6.1.1 Acquiring and Incorporating Bias ..............................91
6.2 Hierarchical Bayesian Lifelong Reinforcement Learning.................92
6.2.1 Motivation......................................................92
6.2.2 Hierarchical Bayesian Approach................................ 93
6.2.3 MTRL Algorithm..................................................93
6.2.4 Updating Hierarchical Model Parameters..........................94
6.2.5 Sampling an MDP................................................ 96
6.3 PG-ELLA: Lifelong Policy Gradient Reinforcement Learning..............96
6.3.1 Policy Gradient Reinforcement Learning ........................97
6.3.2 Policy Gradient Lifelong Learning Setting.......................99
6.3.3 Objective Function and Optimization.............................99
6.3.4 Safe Policy Search for Lifelong Learning...................... 101
6.3.5 Cross-domain Lifelong Reinforcement Learning...................101
6.4 Summary and Evaluation Datasets......................................102
7 Conclusion and Future Directions ...........................................105
Bibliography................................................................Ill
Authors’ Biographies ...................................................... 127
|
| any_adam_object | 1 |
| author | Chen, Zhiyuan Liu, Bing 1963- |
| author_GND | (DE-588)1123153329 (DE-588)1014900026 |
| author_facet | Chen, Zhiyuan Liu, Bing 1963- |
| author_role | aut aut |
| author_sort | Chen, Zhiyuan |
| author_variant | z c zc b l bl |
| building | Verbundindex |
| bvnumber | BV043992760 |
| classification_rvk | ST 302 |
| ctrlnum | (OCoLC)971362622 (DE-599)BVBBV043992760 |
| discipline | Informatik |
| format | Book |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01612nam a2200361 cb4500</leader><controlfield tag="001">BV043992760</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20180914 </controlfield><controlfield tag="007">t|</controlfield><controlfield tag="008">170111s2017 xx |||| 00||| eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781627055017</subfield><subfield code="9">978-1-62705-501-7</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)971362622</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV043992760</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-473</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 302</subfield><subfield code="0">(DE-625)143652:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Chen, Zhiyuan</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)1123153329</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Lifelong Machine Learning</subfield><subfield code="c">Zhiyuan Chen, Google, Inc., Bing Liu, University of Illinois at Chicago</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">San Rafael, California</subfield><subfield code="b">Morgan & Claypool Publishers</subfield><subfield code="c">[2017]</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">XVII, 127 Seiten</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="1" ind2=" "><subfield code="a">Synthesis lectures on artificial intelligence and machine learning</subfield><subfield code="v">33</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Maschinelles Lernen</subfield><subfield code="0">(DE-588)4193754-5</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Maschinelles Lernen</subfield><subfield code="0">(DE-588)4193754-5</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Liu, Bing</subfield><subfield code="d">1963-</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)1014900026</subfield><subfield code="4">aut</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="b">Onlineausgabe</subfield><subfield code="z">978-1-62705-877-3</subfield></datafield><datafield tag="830" ind1=" " ind2="0"><subfield code="a">Synthesis lectures on artificial intelligence and machine learning</subfield><subfield code="v">33</subfield><subfield code="w">(DE-604)BV035750800</subfield><subfield code="9">33</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="m">Digitalisierung UB Bamberg - ADAM Catalogue Enrichment</subfield><subfield code="q">application/pdf</subfield><subfield code="u">http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029400936&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA</subfield><subfield code="3">Inhaltsverzeichnis</subfield></datafield><datafield tag="943" ind1="1" ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-029400936</subfield></datafield></record></collection> |
| id | DE-604.BV043992760 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-20T17:50:41Z |
| institution | BVB |
| isbn | 9781627055017 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029400936 |
| oclc_num | 971362622 |
| open_access_boolean | |
| owner | DE-473 DE-BY-UBG |
| owner_facet | DE-473 DE-BY-UBG |
| physical | XVII, 127 Seiten |
| publishDate | 2017 |
| publishDateSearch | 2017 |
| publishDateSort | 2017 |
| publisher | Morgan & Claypool Publishers |
| record_format | marc |
| series | Synthesis lectures on artificial intelligence and machine learning |
| series2 | Synthesis lectures on artificial intelligence and machine learning |
| spellingShingle | Chen, Zhiyuan Liu, Bing 1963- Lifelong Machine Learning Synthesis lectures on artificial intelligence and machine learning Maschinelles Lernen (DE-588)4193754-5 gnd |
| subject_GND | (DE-588)4193754-5 |
| title | Lifelong Machine Learning |
| title_auth | Lifelong Machine Learning |
| title_exact_search | Lifelong Machine Learning |
| title_full | Lifelong Machine Learning Zhiyuan Chen, Google, Inc., Bing Liu, University of Illinois at Chicago |
| title_fullStr | Lifelong Machine Learning Zhiyuan Chen, Google, Inc., Bing Liu, University of Illinois at Chicago |
| title_full_unstemmed | Lifelong Machine Learning Zhiyuan Chen, Google, Inc., Bing Liu, University of Illinois at Chicago |
| title_short | Lifelong Machine Learning |
| title_sort | lifelong machine learning |
| topic | Maschinelles Lernen (DE-588)4193754-5 gnd |
| topic_facet | Maschinelles Lernen |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029400936&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV035750800 |
| work_keys_str_mv | AT chenzhiyuan lifelongmachinelearning AT liubing lifelongmachinelearning |