Learning in the presence of inaccurate information:
Abstract: "In this paper we discuss the effects of errors in input data on recursion theoretic learning. We consider three types of inaccuracy in input data depending on the presence of extra data (noise), missing data (incompleteness) or both (imperfection). We show that for function learning...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Rochester, NY
1989
|
| Schriftenreihe: | University of Rochester <Rochester, NY> / Department of Computer Science: Technical report
279 |
| Schlagworte: | |
| Zusammenfassung: | Abstract: "In this paper we discuss the effects of errors in input data on recursion theoretic learning. We consider three types of inaccuracy in input data depending on the presence of extra data (noise), missing data (incompleteness) or both (imperfection). We show that for function learning incompleteness harms strictly more than noise. However, for language learning, identification on incomplete text and identification on noisy text are incomparable. We also prove hierarchies based on the number of inaccuracies present in the input." |
| Beschreibung: | 14 S. |
Internformat
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| 100 | 1 | |a Fulk, Mark A. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Learning in the presence of inaccurate information |c Mark A. Fulk and Sanjay Jain |
| 264 | 1 | |a Rochester, NY |c 1989 | |
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| 490 | 1 | |a University of Rochester <Rochester, NY> / Department of Computer Science: Technical report |v 279 | |
| 520 | 3 | |a Abstract: "In this paper we discuss the effects of errors in input data on recursion theoretic learning. We consider three types of inaccuracy in input data depending on the presence of extra data (noise), missing data (incompleteness) or both (imperfection). We show that for function learning incompleteness harms strictly more than noise. However, for language learning, identification on incomplete text and identification on noisy text are incomparable. We also prove hierarchies based on the number of inaccuracies present in the input." | |
| 650 | 4 | |a Data structures (Computer science) | |
| 650 | 4 | |a Input design |x Computers | |
| 700 | 1 | |a Jain, Sanjay |e Verfasser |0 (DE-588)130399949 |4 aut | |
| 810 | 2 | |a Department of Computer Science: Technical report |t University of Rochester <Rochester, NY> |v 279 |w (DE-604)BV008902697 |9 279 | |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-005904690 | ||
Datensatz im Suchindex
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| author | Fulk, Mark A. Jain, Sanjay |
| author_GND | (DE-588)130399949 |
| author_facet | Fulk, Mark A. Jain, Sanjay |
| author_role | aut aut |
| author_sort | Fulk, Mark A. |
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| building | Verbundindex |
| bvnumber | BV008948970 |
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| id | DE-604.BV008948970 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-09T17:27:17Z |
| institution | BVB |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-005904690 |
| oclc_num | 21913942 |
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| physical | 14 S. |
| publishDate | 1989 |
| publishDateSearch | 1989 |
| publishDateSort | 1989 |
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| series2 | University of Rochester <Rochester, NY> / Department of Computer Science: Technical report |
| spelling | Fulk, Mark A. Verfasser aut Learning in the presence of inaccurate information Mark A. Fulk and Sanjay Jain Rochester, NY 1989 14 S. txt rdacontent n rdamedia nc rdacarrier University of Rochester <Rochester, NY> / Department of Computer Science: Technical report 279 Abstract: "In this paper we discuss the effects of errors in input data on recursion theoretic learning. We consider three types of inaccuracy in input data depending on the presence of extra data (noise), missing data (incompleteness) or both (imperfection). We show that for function learning incompleteness harms strictly more than noise. However, for language learning, identification on incomplete text and identification on noisy text are incomparable. We also prove hierarchies based on the number of inaccuracies present in the input." Data structures (Computer science) Input design Computers Jain, Sanjay Verfasser (DE-588)130399949 aut Department of Computer Science: Technical report University of Rochester <Rochester, NY> 279 (DE-604)BV008902697 279 |
| spellingShingle | Fulk, Mark A. Jain, Sanjay Learning in the presence of inaccurate information Data structures (Computer science) Input design Computers |
| title | Learning in the presence of inaccurate information |
| title_auth | Learning in the presence of inaccurate information |
| title_exact_search | Learning in the presence of inaccurate information |
| title_full | Learning in the presence of inaccurate information Mark A. Fulk and Sanjay Jain |
| title_fullStr | Learning in the presence of inaccurate information Mark A. Fulk and Sanjay Jain |
| title_full_unstemmed | Learning in the presence of inaccurate information Mark A. Fulk and Sanjay Jain |
| title_short | Learning in the presence of inaccurate information |
| title_sort | learning in the presence of inaccurate information |
| topic | Data structures (Computer science) Input design Computers |
| topic_facet | Data structures (Computer science) Input design Computers |
| volume_link | (DE-604)BV008902697 |
| work_keys_str_mv | AT fulkmarka learninginthepresenceofinaccurateinformation AT jainsanjay learninginthepresenceofinaccurateinformation |