Learning with Partially Labeled and Interdependent Data:
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cham
Springer
2015
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| Subjects: | |
| Online Access: | DE-634 DE-Aug4 DE-573 DE-M347 DE-92 DE-859 DE-860 DE-861 DE-473 DE-19 DE-355 DE-703 DE-20 DE-29 DE-739 Volltext Inhaltsverzeichnis Abstract |
| Physical Description: | 1 Online-Ressource (XIII, 106 Seiten) Illustrationen |
| ISBN: | 9783319157269 |
| DOI: | 10.1007/978-3-319-15726-9 |
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Record in the Search Index
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| adam_text |
LEARNING WITH PARTIALLY LABELED AND INTERDEPENDENT DATA
/ AMINI, MASSIH-REZA
: 2015
TABLE OF CONTENTS / INHALTSVERZEICHNIS
INTRODUCTION
INTRODUCTION TO LEARNING THEORY
SEMI-SUPERVISED LEARNING
LEARNING WITH INTERDEPENDENT DATA
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT.
LEARNING WITH PARTIALLY LABELED AND INTERDEPENDENT DATA
/ AMINI, MASSIH-REZA
: 2015
ABSTRACT / INHALTSTEXT
THIS BOOK DEVELOPS TWO KEY MACHINE LEARNING PRINCIPLES: THE
SEMI-SUPERVISED PARADIGM AND LEARNING WITH INTERDEPENDENT DATA. IT
REVEALS NEW APPLICATIONS, PRIMARILY WEB RELATED, THAT TRANSGRESS THE
CLASSICAL MACHINE LEARNING FRAMEWORK THROUGH LEARNING WITH
INTERDEPENDENT DATA. THE BOOK TRACES HOW THE SEMI-SUPERVISED PARADIGM
AND THE LEARNING TO RANK PARADIGM EMERGED FROM NEW WEB APPLICATIONS,
LEADING TO A MASSIVE PRODUCTION OF HETEROGENEOUS TEXTUAL DATA. IT
EXPLAINS HOW SEMI-SUPERVISED LEARNING TECHNIQUES ARE WIDELY USED, BUT
ONLY ALLOW A LIMITED ANALYSIS OF THE INFORMATION CONTENT AND THUS DO NOT
MEET THE DEMANDS OF MANY WEB-RELATED TASKS. LATER CHAPTERS DEAL WITH THE
DEVELOPMENT OF LEARNING METHODS FOR RANKING ENTITIES IN A LARGE
COLLECTION WITH RESPECT TO PRECISE INFORMATION NEEDED. IN SOME CASES,
LEARNING A RANKING FUNCTION CAN BE REDUCED TO LEARNING A CLASSIFICATION
FUNCTION OVER THE PAIRS OF EXAMPLES. THE BOOK PROVES THAT THIS TASK CAN
BE EFFICIENTLY TACKLED IN A NEW FRAMEWORK: LEARNING WITH INTERDEPENDENT
DATA. RESEARCHERS AND PROFESSIONALS IN MACHINE LEARNING WILL FIND THESE
NEW PERSPECTIVES AND SOLUTIONS VALUABLE. LEARNING WITH PARTIALLY LABELED
AND INTERDEPENDENT DATA IS ALSO USEFUL FOR ADVANCED-LEVEL STUDENTS OF
COMPUTER SCIENCE, PARTICULARLY THOSE FOCUSED ON STATISTICS AND LEARNING
DIESES SCHRIFTSTUECK WURDE MASCHINELL ERZEUGT. |
| any_adam_object | 1 |
| author | Amini, Massih-Reza Usunier, Nicolas |
| author_GND | (DE-588)109846088X (DE-588)1098461010 |
| author_facet | Amini, Massih-Reza Usunier, Nicolas |
| author_role | aut aut |
| author_sort | Amini, Massih-Reza |
| author_variant | m r a mra n u nu |
| building | Verbundindex |
| bvnumber | BV042592133 |
| classification_rvk | ST 300 |
| collection | ZDB-2-SCS |
| ctrlnum | (OCoLC)910743096 (DE-599)BVBBV042592133 |
| dewey-full | 004 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 004 - Computer science |
| dewey-raw | 004 |
| dewey-search | 004 |
| dewey-sort | 14 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| doi_str_mv | 10.1007/978-3-319-15726-9 |
| format | Electronic eBook |
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| language | English |
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| spelling | Amini, Massih-Reza Verfasser (DE-588)109846088X aut Learning with Partially Labeled and Interdependent Data by Massih-Reza Amini, Nicolas Usunier Cham Springer 2015 1 Online-Ressource (XIII, 106 Seiten) Illustrationen txt rdacontent c rdamedia cr rdacarrier Künstliche Intelligenz (DE-588)4033447-8 gnd rswk-swf Data Mining (DE-588)4428654-5 gnd rswk-swf Informatik (DE-588)4026894-9 gnd rswk-swf Informatik (DE-588)4026894-9 s Künstliche Intelligenz (DE-588)4033447-8 s Data Mining (DE-588)4428654-5 s DE-604 Usunier, Nicolas Verfasser (DE-588)1098461010 aut Erscheint auch als Druckausgabe 978-3-319-15725-2 https://doi.org/10.1007/978-3-319-15726-9 Verlag URL des Erstveröffentlichers Volltext Springer Fremddatenuebernahme application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028025345&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Springer Fremddatenuebernahme application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028025345&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Abstract |
| spellingShingle | Amini, Massih-Reza Usunier, Nicolas Learning with Partially Labeled and Interdependent Data Künstliche Intelligenz (DE-588)4033447-8 gnd Data Mining (DE-588)4428654-5 gnd Informatik (DE-588)4026894-9 gnd |
| subject_GND | (DE-588)4033447-8 (DE-588)4428654-5 (DE-588)4026894-9 |
| title | Learning with Partially Labeled and Interdependent Data |
| title_auth | Learning with Partially Labeled and Interdependent Data |
| title_exact_search | Learning with Partially Labeled and Interdependent Data |
| title_full | Learning with Partially Labeled and Interdependent Data by Massih-Reza Amini, Nicolas Usunier |
| title_fullStr | Learning with Partially Labeled and Interdependent Data by Massih-Reza Amini, Nicolas Usunier |
| title_full_unstemmed | Learning with Partially Labeled and Interdependent Data by Massih-Reza Amini, Nicolas Usunier |
| title_short | Learning with Partially Labeled and Interdependent Data |
| title_sort | learning with partially labeled and interdependent data |
| topic | Künstliche Intelligenz (DE-588)4033447-8 gnd Data Mining (DE-588)4428654-5 gnd Informatik (DE-588)4026894-9 gnd |
| topic_facet | Künstliche Intelligenz Data Mining Informatik |
| url | https://doi.org/10.1007/978-3-319-15726-9 http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028025345&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028025345&sequence=000003&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT aminimassihreza learningwithpartiallylabeledandinterdependentdata AT usuniernicolas learningwithpartiallylabeledandinterdependentdata |