Machine Learning: A Guide to Current Research
One of the currently most active research areas within Artificial Intelligence is the field of Machine Learning. which involves the study and development of computational models of learning processes. A major goal of research in this field is to build computers capable of improving their performance...
Gespeichert in:
| Beteiligte Personen: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Boston, MA
Springer US
1986
|
| Schriftenreihe: | The Kluwer International Series in Engineering and Computer Science, Knowledge Representation, Learning and Expert Systems
12 |
| Schlagwörter: | |
| Links: | https://doi.org/10.1007/978-1-4613-2279-5 https://doi.org/10.1007/978-1-4613-2279-5 |
| Zusammenfassung: | One of the currently most active research areas within Artificial Intelligence is the field of Machine Learning. which involves the study and development of computational models of learning processes. A major goal of research in this field is to build computers capable of improving their performance with practice and of acquiring knowledge on their own. The intent of this book is to provide a snapshot of this field through a broad. representative set of easily assimilated short papers. As such. this book is intended to complement the two volumes of Machine Learning: An Artificial Intelligence Approach (Morgan-Kaufman Publishers). which provide a smaller number of in-depth research papers. Each of the 77 papers in the present book summarizes a current research effort. and provides references to longer expositions appearing elsewhere. These papers cover a broad range of topics. including research on analogy. conceptual clustering. explanation-based generalization. incremental learning. inductive inference. learning apprentice systems. machine discovery. theoretical models of learning. and applications of machine learning methods. A subject index IS provided to assist in locating research related to specific topics. The majority of these papers were collected from the participants at the Third International Machine Learning Workshop. held June 24-26. 1985 at Skytop Lodge. Skytop. Pennsylvania. While the list of research projects covered is not exhaustive. we believe that it provides a representative sampling of the best ongoing work in the field. and a unique perspective on where the field is and where it is headed |
| Umfang: | 1 Online-Ressource (XVI, 429 p) |
| ISBN: | 9781461322795 |
| DOI: | 10.1007/978-1-4613-2279-5 |
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| 520 | |a One of the currently most active research areas within Artificial Intelligence is the field of Machine Learning. which involves the study and development of computational models of learning processes. A major goal of research in this field is to build computers capable of improving their performance with practice and of acquiring knowledge on their own. The intent of this book is to provide a snapshot of this field through a broad. representative set of easily assimilated short papers. As such. this book is intended to complement the two volumes of Machine Learning: An Artificial Intelligence Approach (Morgan-Kaufman Publishers). which provide a smaller number of in-depth research papers. Each of the 77 papers in the present book summarizes a current research effort. and provides references to longer expositions appearing elsewhere. These papers cover a broad range of topics. including research on analogy. conceptual clustering. explanation-based generalization. incremental learning. inductive inference. learning apprentice systems. machine discovery. theoretical models of learning. and applications of machine learning methods. A subject index IS provided to assist in locating research related to specific topics. The majority of these papers were collected from the participants at the Third International Machine Learning Workshop. held June 24-26. 1985 at Skytop Lodge. Skytop. Pennsylvania. While the list of research projects covered is not exhaustive. we believe that it provides a representative sampling of the best ongoing work in the field. and a unique perspective on where the field is and where it is headed | ||
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Datensatz im Suchindex
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| author | Mitchell, Tom M. Carbonell, Jaime G. Michalski, Ryszard S. 1937-2007 |
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| dewey-full | 006.3 |
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| discipline | Informatik |
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| spelling | Mitchell, Tom M. Verfasser aut Machine Learning A Guide to Current Research by Tom M. Mitchell, Jaime G. Carbonell, Ryszard S. Michalski Boston, MA Springer US 1986 1 Online-Ressource (XVI, 429 p) txt rdacontent c rdamedia cr rdacarrier The Kluwer International Series in Engineering and Computer Science, Knowledge Representation, Learning and Expert Systems 12 One of the currently most active research areas within Artificial Intelligence is the field of Machine Learning. which involves the study and development of computational models of learning processes. A major goal of research in this field is to build computers capable of improving their performance with practice and of acquiring knowledge on their own. The intent of this book is to provide a snapshot of this field through a broad. representative set of easily assimilated short papers. As such. this book is intended to complement the two volumes of Machine Learning: An Artificial Intelligence Approach (Morgan-Kaufman Publishers). which provide a smaller number of in-depth research papers. Each of the 77 papers in the present book summarizes a current research effort. and provides references to longer expositions appearing elsewhere. These papers cover a broad range of topics. including research on analogy. conceptual clustering. explanation-based generalization. incremental learning. inductive inference. learning apprentice systems. machine discovery. theoretical models of learning. and applications of machine learning methods. A subject index IS provided to assist in locating research related to specific topics. The majority of these papers were collected from the participants at the Third International Machine Learning Workshop. held June 24-26. 1985 at Skytop Lodge. Skytop. Pennsylvania. While the list of research projects covered is not exhaustive. we believe that it provides a representative sampling of the best ongoing work in the field. and a unique perspective on where the field is and where it is headed Computer Science Artificial Intelligence (incl. Robotics) Computer science Artificial intelligence Künstliche Intelligenz (DE-588)4033447-8 gnd rswk-swf Lernender Automat (DE-588)4167398-0 gnd rswk-swf 1\p (DE-588)4143413-4 Aufsatzsammlung gnd-content Künstliche Intelligenz (DE-588)4033447-8 s 2\p DE-604 Lernender Automat (DE-588)4167398-0 s 3\p DE-604 Carbonell, Jaime G. aut Michalski, Ryszard S. 1937-2007 (DE-588)11030196X aut Erscheint auch als Druck-Ausgabe 9781461294061 https://doi.org/10.1007/978-1-4613-2279-5 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 3\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Mitchell, Tom M. Carbonell, Jaime G. Michalski, Ryszard S. 1937-2007 Machine Learning A Guide to Current Research Computer Science Artificial Intelligence (incl. Robotics) Computer science Artificial intelligence Künstliche Intelligenz (DE-588)4033447-8 gnd Lernender Automat (DE-588)4167398-0 gnd |
| subject_GND | (DE-588)4033447-8 (DE-588)4167398-0 (DE-588)4143413-4 |
| title | Machine Learning A Guide to Current Research |
| title_auth | Machine Learning A Guide to Current Research |
| title_exact_search | Machine Learning A Guide to Current Research |
| title_full | Machine Learning A Guide to Current Research by Tom M. Mitchell, Jaime G. Carbonell, Ryszard S. Michalski |
| title_fullStr | Machine Learning A Guide to Current Research by Tom M. Mitchell, Jaime G. Carbonell, Ryszard S. Michalski |
| title_full_unstemmed | Machine Learning A Guide to Current Research by Tom M. Mitchell, Jaime G. Carbonell, Ryszard S. Michalski |
| title_short | Machine Learning |
| title_sort | machine learning a guide to current research |
| title_sub | A Guide to Current Research |
| topic | Computer Science Artificial Intelligence (incl. Robotics) Computer science Artificial intelligence Künstliche Intelligenz (DE-588)4033447-8 gnd Lernender Automat (DE-588)4167398-0 gnd |
| topic_facet | Computer Science Artificial Intelligence (incl. Robotics) Computer science Artificial intelligence Künstliche Intelligenz Lernender Automat Aufsatzsammlung |
| url | https://doi.org/10.1007/978-1-4613-2279-5 |
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