|
|
|
|
LEADER |
10647cam a2201453 4500 |
001 |
183-595126758 |
003 |
DE-627 |
005 |
20240214204718.0 |
007 |
cr uuu---uuuuu |
008 |
090328s1993 gw |||||o 00| ||eng c |
020 |
|
|
|a 9783540475682
|9 978-3-540-47568-2
|
024 |
7 |
|
|a 10.1007/3-540-56483-7
|2 doi
|
035 |
|
|
|a (DE-627)595126758
|
035 |
|
|
|a (DE-576)9595126756
|
035 |
|
|
|a (DE-599)GBV595126758
|
035 |
|
|
|a (DE-601)NLM00372154X
|
035 |
|
|
|a (ZBM)0825.00048
|
035 |
|
|
|a (ZBM)0825.00048
|
035 |
|
|
|a (DE-He213)978-3-540-47568-2
|
035 |
|
|
|a (EBP)040474402
|
040 |
|
|
|a DE-627
|b ger
|c DE-627
|e rakwb
|
041 |
|
|
|a eng
|
044 |
|
|
|c XA-DE-BE
|
050 |
|
0 |
|a Q325.5
|
072 |
|
7 |
|a UYQ
|2 bicssc
|
072 |
|
7 |
|a COM004000
|2 bisacsh
|
084 |
|
|
|a 28
|2 sdnb
|
084 |
|
|
|a ST 285
|q SEPA
|2 rvk
|0 (DE-625)rvk/143648:
|
084 |
|
|
|a SS 4800
|q SEPA
|2 rvk
|0 (DE-625)rvk/143528:
|
084 |
|
|
|a ST 300
|q SEPA
|2 rvk
|0 (DE-625)rvk/143650:
|
084 |
|
|
|a *00B15
|2 msc
|
084 |
|
|
|a 68-06
|2 msc
|
084 |
|
|
|a 54.10
|2 bkl
|
084 |
|
|
|a 54.72
|2 bkl
|
245 |
1 |
0 |
|a Machine learning
|b from theory to applications ; cooperative research at Siemens and MIT
|c S. J. Hanson ... (eds.)
|
264 |
|
1 |
|a Berlin [u.a.]
|b Springer
|c 1993
|
300 |
|
|
|a Online-Ressource (VIII, 271 S.)
|
336 |
|
|
|a Text
|b txt
|2 rdacontent
|
337 |
|
|
|a Computermedien
|b c
|2 rdamedia
|
338 |
|
|
|a Online-Ressource
|b cr
|2 rdacarrier
|
490 |
1 |
|
|a Lecture notes in computer science
|v 661
|
500 |
|
|
|a Literaturangaben
|
520 |
|
|
|a Strategic directions in machine learning -- Training a 3-node neural network is NP-complete -- Cryptographic limitations on learning Boolean formulae and finite automata -- Inference of finite automata using homing sequences -- Adaptive search by learning from incomplete explanations of failures -- Learning of rules for fault diagnosis in power supply networks -- Cross references are features -- The schema mechanism -- L-ATMS: A tight integration of EBL and the ATMS -- Massively parallel symbolic induction of protein structure/function relationships -- Task decomposition through competition in a modular connectionist architecture: The what and where vision tasks -- Phoneme discrimination using connectionist networks -- Behavior-based learning to control IR oven heating: Preliminary investigations -- Trellis codes, receptive fields, and fault tolerant, self-repairing neural networks.
|
520 |
|
|
|a This volume includes some of the key research papers in the area of machine learning produced at MIT and Siemens during a three-year joint research effort. It includes papers on many different styles of machine learning, organized into three parts. Part I, theory, includes three papers on theoretical aspects of machine learning. The first two use the theory of computational complexity to derive some fundamental limits on what isefficiently learnable. The third provides an efficient algorithm for identifying finite automata. Part II, artificial intelligence and symbolic learning methods, includes five papers giving an overview of the state of the art and future developments in the field of machine learning, a subfield of artificial intelligence dealing with automated knowledge acquisition and knowledge revision. Part III, neural and collective computation, includes five papers sampling the theoretical diversity and trends in the vigorous new research field of neural networks: massively parallel symbolic induction, task decomposition through competition, phoneme discrimination, behavior-based learning, and self-repairing neural networks.
|
533 |
|
|
|a Online-Ausg.
|b Berlin [u.a.]
|c Springer
|d 2006
|f Springer lecture notes archive
|7 |2006||||||||||
|
650 |
|
0 |
|a Machine learning
|x Congresses
|
650 |
|
0 |
|a Artificial intelligence
|x Congresses
|
650 |
|
0 |
|a Neural networks (Computer science)
|x Congresses
|
650 |
|
0 |
|a Computer science
|
650 |
|
0 |
|a Artificial intelligence
|
650 |
|
0 |
|a Microprocessors.
|
650 |
|
0 |
|a Computer architecture.
|
650 |
|
4 |
|a Computation by Abstract Devices
|
650 |
|
4 |
|a Computer Science
|
650 |
|
4 |
|a Processor Architectures
|
650 |
|
4 |
|a Artificial Intelligence (incl. Robotics)
|
650 |
|
4 |
|a Informatik
|
650 |
|
4 |
|a Informationsverarbeitung
|
650 |
|
4 |
|a Künstliche Intelligenz
|
650 |
|
4 |
|a Lerntheorie
|
653 |
|
0 |
|a Machine
|a Congresses
|
653 |
|
0 |
|a Artificial
|a Congresses
|
653 |
|
0 |
|a Neural
|a Congresses
|
655 |
|
7 |
|a Aufsatzsammlung
|0 (DE-588)4143413-4
|0 (DE-627)105605727
|0 (DE-576)209726091
|2 gnd-content
|
689 |
0 |
0 |
|D s
|0 (DE-588)4193754-5
|0 (DE-627)105224782
|0 (DE-576)21008944X
|a Maschinelles Lernen
|2 gnd
|
689 |
0 |
|
|5 DE-101
|
700 |
1 |
|
|a Hanson, Stephen José
|4 oth
|
776 |
1 |
|
|z 3540564837
|
776 |
1 |
|
|z 9783540564836
|
776 |
0 |
8 |
|i Druckausg.
|t Machine learning
|d Berlin : Springer, 1993
|h VIII, 271 S.
|w (DE-627)122687868
|w (DE-576)032837437
|z 3540564837
|z 0387564837
|
830 |
|
0 |
|a Lecture notes in computer science
|v 661
|9 66100
|w (DE-627)316228877
|w (DE-576)093890923
|w (DE-600)2018930-8
|x 1611-3349
|7 ns
|
856 |
4 |
0 |
|u http://www.springerlink.com/content/ul47l844n871
|x Verlag
|z lizenzpflichtig
|3 Volltext
|
856 |
4 |
0 |
|u http://www.springerlink.de/openurl.asp?genre=book&isbn=978-3-540-56483-6
|x Verlag
|z lizenzpflichtig
|3 Volltext
|
856 |
4 |
0 |
|u http://dx.doi.org/10.1007/3-540-56483-7
|x Resolving-System
|z lizenzpflichtig
|3 Volltext
|
856 |
4 |
0 |
|u https://doi.org/10.1007/3-540-56483-7
|m X:SPRINGER
|x Resolving-System
|z lizenzpflichtig
|
856 |
4 |
2 |
|u https://zbmath.org/?q=an:0825.00048
|m B:ZBM
|v 2021-04-12
|x Verlag
|y Zentralblatt MATH
|3 Inhaltstext
|
912 |
|
|
|a ZDB-1-SLN
|
912 |
|
|
|a ZDB-2-LNC
|b 1993
|
912 |
|
|
|a ZDB-2-SCS
|b 1993
|
912 |
|
|
|a ZDB-2-BAE
|b 1993
|
912 |
|
|
|a ZDB-2-SXCS
|b 1993
|
912 |
|
|
|a ZDB-2-SEB
|b 1993
|
912 |
|
|
|a SSG-OPC-mat
|
924 |
1 |
|
|a 1221298623
|b DE-1a
|9 1a
|c GBV
|d d
|h 5:INTERN
|k http://erf.sbb.spk-berlin.de/han/512881081/dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 202667081
|b DE-84
|9 84
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 201777320
|b DE-46
|9 46
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 1162771437
|b DE-18
|9 18
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|k http://emedien.sub.uni-hamburg.de/han/SpringerEbooks/dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 202426335
|b DE-830
|9 830
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 20269075X
|b DE-8
|9 8
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 3503727167
|b DE-104
|9 104
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 1114763802
|b DE-27
|9 27
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 202731901
|b DE-Ilm1
|9 Ilm 1
|c GBV
|d d
|g Online-Ressource
|h Internet
|
924 |
1 |
|
|a 127348729X
|b DE-7
|9 7
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|k http://han.sub.uni-goettingen.de/han/SpringerLectureNotesinComputerScience/dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 1159774412
|b DE-705
|9 705
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 202643409
|b DE-28
|9 28
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 202702588
|b DE-Wim2
|9 Wim 2
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 202631567
|b DE-3
|9 3
|c GBV
|d d
|g ebook
|k http://dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 1173496769
|b DE-9
|9 9
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 1670357139
|b DE-95
|9 95
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 1196440972
|b DE-Ma9
|9 Ma 9
|c GBV
|d d
|g ebook SpringerLectureNotes
|k http://dx.doi.org/10.1007/3-540-56483-7
|k http://han.med.uni-magdeburg.de/han/NLUNIeBookSpringerLectureNotes/dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 1196477515
|b DE-Ma14
|9 Ma 14
|c GBV
|d d
|g ebook SpringerLectureNotes
|k http://dx.doi.org/10.1007/3-540-56483-7
|k http://han.med.uni-magdeburg.de/han/NLUNIeBookSpringerLectureNotes/dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 1217416587
|b DE-Luen4
|9 Lün 4
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 1586808761
|b DE-Kt1
|9 Kt 1
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 927646153
|b DE-715
|9 715
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 1753261228
|b DE-715
|9 715
|c GBV
|d d
|k http://49gbv-uob-primo.hosted.exlibrisgroup.com/openurl/49GBV_UOB/UOB_services_page?u.ignore_date_coverage=true&rft.mms_id=991010473249703501
|l Springer Lecture Notes [Nationallizenz]
|l Campusweiter Zugriff (Universität Oldenburg). - Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden.
|
924 |
1 |
|
|a 202655245
|b DE-700
|9 700
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 3848426250
|b DE-Wis1
|9 Wis 1
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 1263874665
|b DE-755
|9 755
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 1172947740
|b DE-960
|9 960
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 203361911
|b DE-916
|9 916
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 1823528023
|b DE-Ki95
|9 Ki 95
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 1222077086
|b DE-H155
|9 H 155
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 202678911
|b DE-517
|9 517
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 1172991480
|b DE-960-3
|9 960/3
|c GBV
|d d
|k http://dx.doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 4484379031
|b DE-14
|9 14
|c BSZ
|d d
|k https://doi.org/10.1007/3-540-56483-7
|
924 |
1 |
|
|a 448437904X
|b DE-576
|9 576
|c BSZ
|d d
|
924 |
1 |
|
|a 4484338653
|b DE-Ofb1
|9 Ofb 1
|c BSZ
|d d
|g E-Book Springer
|k https://doi.org/10.1007/3-540-56483-7
|l Zum Online-Dokument
|l Zugang im Hochschulnetz der HS Offenburg / extern via VPN oder Shibboleth (Login über Institution)
|
936 |
r |
v |
|a ST 285
|b Computer supported cooperative work (CSCW), Groupware
|k Informatik
|k Monografien
|k Software und -entwicklung
|k Computer supported cooperative work (CSCW), Groupware
|0 (DE-627)1270877453
|0 (DE-625)rvk/143648:
|0 (DE-576)200877453
|
936 |
r |
v |
|a SS 4800
|b Lecture notes in computer science
|k Informatik
|k Enzyklopädien und Handbücher. Kongressberichte Schriftenreihe. Tafeln und Formelsammlungen
|k Schriftenreihen (indiv. Sign.)
|k Lecture notes in computer science
|0 (DE-627)1271461242
|0 (DE-625)rvk/143528:
|0 (DE-576)201461242
|
936 |
r |
v |
|a ST 300
|b Allgemeines
|k Informatik
|k Monografien
|k Künstliche Intelligenz
|k Allgemeines
|0 (DE-627)1271119005
|0 (DE-625)rvk/143650:
|0 (DE-576)201119005
|
936 |
b |
k |
|a 54.10
|j Theoretische Informatik
|0 (DE-627)106418815
|
936 |
b |
k |
|a 54.72
|j Künstliche Intelligenz
|0 (DE-627)10641240X
|
951 |
|
|
|a BO
|
980 |
|
|
|a 595126758
|b 183
|c sid-183-col-kxpbbi
|
SOLR
_version_ |
1797248075857657856 |
author2 |
Hanson, Stephen José |
author2_role |
oth |
author2_variant |
s j h sj sjh |
author_facet |
Hanson, Stephen José |
building |
Library A |
callnumber-first |
Q - Science |
callnumber-label |
Q325 |
callnumber-raw |
Q325.5 |
callnumber-search |
Q325.5 |
callnumber-sort |
Q 3325.5 |
callnumber-subject |
Q - General Science |
collection |
ZDB-1-SLN, ZDB-2-LNC, ZDB-2-SCS, ZDB-2-BAE, ZDB-2-SXCS, ZDB-2-SEB, SSG-OPC-mat, sid-183-col-kxpbbi |
contents |
Strategic directions in machine learning -- Training a 3-node neural network is NP-complete -- Cryptographic limitations on learning Boolean formulae and finite automata -- Inference of finite automata using homing sequences -- Adaptive search by learning from incomplete explanations of failures -- Learning of rules for fault diagnosis in power supply networks -- Cross references are features -- The schema mechanism -- L-ATMS: A tight integration of EBL and the ATMS -- Massively parallel symbolic induction of protein structure/function relationships -- Task decomposition through competition in a modular connectionist architecture: The what and where vision tasks -- Phoneme discrimination using connectionist networks -- Behavior-based learning to control IR oven heating: Preliminary investigations -- Trellis codes, receptive fields, and fault tolerant, self-repairing neural networks., This volume includes some of the key research papers in the area of machine learning produced at MIT and Siemens during a three-year joint research effort. It includes papers on many different styles of machine learning, organized into three parts. Part I, theory, includes three papers on theoretical aspects of machine learning. The first two use the theory of computational complexity to derive some fundamental limits on what isefficiently learnable. The third provides an efficient algorithm for identifying finite automata. Part II, artificial intelligence and symbolic learning methods, includes five papers giving an overview of the state of the art and future developments in the field of machine learning, a subfield of artificial intelligence dealing with automated knowledge acquisition and knowledge revision. Part III, neural and collective computation, includes five papers sampling the theoretical diversity and trends in the vigorous new research field of neural networks: massively parallel symbolic induction, task decomposition through competition, phoneme discrimination, behavior-based learning, and self-repairing neural networks. |
ctrlnum |
(DE-627)595126758, (DE-576)9595126756, (DE-599)GBV595126758, (DE-601)NLM00372154X, (ZBM)0825.00048, (DE-He213)978-3-540-47568-2, (EBP)040474402 |
doi_str_mv |
10.1007/3-540-56483-7 |
facet_912a |
ZDB-1-SLN, ZDB-2-LNC, ZDB-2-SCS, ZDB-2-BAE, ZDB-2-SXCS, ZDB-2-SEB, SSG-OPC-mat |
facet_avail |
Online |
facet_local_del330 |
Maschinelles Lernen |
facet_topic_nrw_music |
Machine, Congresses, Artificial, Neural |
finc_class_facet |
Informatik, Allgemeine Naturwissenschaft |
fincclass_txtF_mv |
science-computerscience |
footnote |
Literaturangaben |
format |
eBook |
format_access_txtF_mv |
Book, E-Book |
format_de105 |
Ebook |
format_de14 |
Book, E-Book |
format_de15 |
Book, E-Book |
format_del152 |
Buch |
format_detail_txtF_mv |
text-online-monograph-independent |
format_dezi4 |
e-Book |
format_finc |
Book, E-Book |
format_legacy |
ElectronicBook |
format_legacy_nrw |
Book, E-Book |
format_nrw |
Book, E-Book |
format_strict_txtF_mv |
E-Book |
genre |
Aufsatzsammlung (DE-588)4143413-4 (DE-627)105605727 (DE-576)209726091 gnd-content |
genre_facet |
Aufsatzsammlung |
geogr_code |
not assigned |
geogr_code_person |
not assigned |
hierarchy_parent_id |
183-316228877 |
hierarchy_parent_title |
Lecture notes in computer science |
hierarchy_sequence |
66100 |
hierarchy_top_id |
183-316228877 |
hierarchy_top_title |
Lecture notes in computer science |
id |
183-595126758 |
illustrated |
Not Illustrated |
imprint |
Berlin [u.a.], Springer, 1993 |
imprint_str_mv |
Berlin [u.a.]: Springer, 1993, Online-Ausg.: Berlin [u.a.]: Springer, 2006 |
institution |
FID-BBI-DE-23 |
is_hierarchy_id |
183-595126758 |
is_hierarchy_title |
Machine learning: from theory to applications ; cooperative research at Siemens and MIT |
isbn |
9783540475682 |
isbn_isn_mv |
3540564837, 9783540564836, 0387564837 |
issn_isn_mv |
1611-3349 |
language |
English |
last_indexed |
2024-04-24T20:08:49.865Z |
marc024a_ct_mv |
10.1007/3-540-56483-7 |
marc_error |
[geogr_code]Unable to make public java.lang.AbstractStringBuilder java.lang.AbstractStringBuilder.append(java.lang.String) accessible: module java.base does not "opens java.lang" to unnamed module @6684697a |
match_str |
hanson1993machinelearningfromtheorytoapplicationscooperativeresearchatsiemensandmit |
mega_collection |
K10plus Verbundkatalog, Springer Lecture Notes |
multipart_link |
093890923 |
multipart_part |
(093890923)661 |
physical |
Online-Ressource (VIII, 271 S.) |
publishDate |
1993 |
publishDateSort |
1993 |
publishPlace |
Berlin [u.a.] |
publisher |
Springer |
record_format |
marcfinc |
record_id |
595126758 |
recordtype |
marcfinc |
rvk_facet |
ST 285, SS 4800, ST 300 |
rvk_label |
Informatik, Monografien, Software und -entwicklung, Computer supported cooperative work (CSCW), Groupware, Enzyklopädien und Handbücher. Kongressberichte Schriftenreihe. Tafeln und Formelsammlungen, Schriftenreihen (indiv. Sign.), Lecture notes in computer science, Künstliche Intelligenz, Allgemeines |
rvk_path |
SS, ST, ST 285, SQ - SU, SS 4000 - SS 5999, ST 300, SS 4800, ST 300 - ST 308, ST 230 - ST 285 |
rvk_path_str_mv |
SS, ST, ST 285, SQ - SU, SS 4000 - SS 5999, ST 300, SS 4800, ST 300 - ST 308, ST 230 - ST 285 |
series |
Lecture notes in computer science, 661 |
series2 |
Lecture notes in computer science ; 661 |
source_id |
183 |
spelling |
Machine learning from theory to applications ; cooperative research at Siemens and MIT S. J. Hanson ... (eds.), Berlin [u.a.] Springer 1993, Online-Ressource (VIII, 271 S.), Text txt rdacontent, Computermedien c rdamedia, Online-Ressource cr rdacarrier, Lecture notes in computer science 661, Literaturangaben, Strategic directions in machine learning -- Training a 3-node neural network is NP-complete -- Cryptographic limitations on learning Boolean formulae and finite automata -- Inference of finite automata using homing sequences -- Adaptive search by learning from incomplete explanations of failures -- Learning of rules for fault diagnosis in power supply networks -- Cross references are features -- The schema mechanism -- L-ATMS: A tight integration of EBL and the ATMS -- Massively parallel symbolic induction of protein structure/function relationships -- Task decomposition through competition in a modular connectionist architecture: The what and where vision tasks -- Phoneme discrimination using connectionist networks -- Behavior-based learning to control IR oven heating: Preliminary investigations -- Trellis codes, receptive fields, and fault tolerant, self-repairing neural networks., This volume includes some of the key research papers in the area of machine learning produced at MIT and Siemens during a three-year joint research effort. It includes papers on many different styles of machine learning, organized into three parts. Part I, theory, includes three papers on theoretical aspects of machine learning. The first two use the theory of computational complexity to derive some fundamental limits on what isefficiently learnable. The third provides an efficient algorithm for identifying finite automata. Part II, artificial intelligence and symbolic learning methods, includes five papers giving an overview of the state of the art and future developments in the field of machine learning, a subfield of artificial intelligence dealing with automated knowledge acquisition and knowledge revision. Part III, neural and collective computation, includes five papers sampling the theoretical diversity and trends in the vigorous new research field of neural networks: massively parallel symbolic induction, task decomposition through competition, phoneme discrimination, behavior-based learning, and self-repairing neural networks., Online-Ausg. Berlin [u.a.] Springer 2006 Springer lecture notes archive |2006||||||||||, Machine learning Congresses, Artificial intelligence Congresses, Neural networks (Computer science) Congresses, Computer science, Artificial intelligence, Microprocessors., Computer architecture., Computation by Abstract Devices, Computer Science, Processor Architectures, Artificial Intelligence (incl. Robotics), Informatik, Informationsverarbeitung, Künstliche Intelligenz, Lerntheorie, Machine Congresses, Artificial Congresses, Neural Congresses, Aufsatzsammlung (DE-588)4143413-4 (DE-627)105605727 (DE-576)209726091 gnd-content, s (DE-588)4193754-5 (DE-627)105224782 (DE-576)21008944X Maschinelles Lernen gnd, DE-101, Hanson, Stephen José oth, 3540564837, 9783540564836, Druckausg. Machine learning Berlin : Springer, 1993 VIII, 271 S. (DE-627)122687868 (DE-576)032837437 3540564837 0387564837, Lecture notes in computer science 661 66100 (DE-627)316228877 (DE-576)093890923 (DE-600)2018930-8 1611-3349 ns, http://www.springerlink.com/content/ul47l844n871 Verlag lizenzpflichtig Volltext, http://www.springerlink.de/openurl.asp?genre=book&isbn=978-3-540-56483-6 Verlag lizenzpflichtig Volltext, http://dx.doi.org/10.1007/3-540-56483-7 Resolving-System lizenzpflichtig Volltext, https://doi.org/10.1007/3-540-56483-7 X:SPRINGER Resolving-System lizenzpflichtig, https://zbmath.org/?q=an:0825.00048 B:ZBM 2021-04-12 Verlag Zentralblatt MATH Inhaltstext |
spellingShingle |
Machine learning: from theory to applications ; cooperative research at Siemens and MIT, Lecture notes in computer science, 661, Strategic directions in machine learning -- Training a 3-node neural network is NP-complete -- Cryptographic limitations on learning Boolean formulae and finite automata -- Inference of finite automata using homing sequences -- Adaptive search by learning from incomplete explanations of failures -- Learning of rules for fault diagnosis in power supply networks -- Cross references are features -- The schema mechanism -- L-ATMS: A tight integration of EBL and the ATMS -- Massively parallel symbolic induction of protein structure/function relationships -- Task decomposition through competition in a modular connectionist architecture: The what and where vision tasks -- Phoneme discrimination using connectionist networks -- Behavior-based learning to control IR oven heating: Preliminary investigations -- Trellis codes, receptive fields, and fault tolerant, self-repairing neural networks., This volume includes some of the key research papers in the area of machine learning produced at MIT and Siemens during a three-year joint research effort. It includes papers on many different styles of machine learning, organized into three parts. Part I, theory, includes three papers on theoretical aspects of machine learning. The first two use the theory of computational complexity to derive some fundamental limits on what isefficiently learnable. The third provides an efficient algorithm for identifying finite automata. Part II, artificial intelligence and symbolic learning methods, includes five papers giving an overview of the state of the art and future developments in the field of machine learning, a subfield of artificial intelligence dealing with automated knowledge acquisition and knowledge revision. Part III, neural and collective computation, includes five papers sampling the theoretical diversity and trends in the vigorous new research field of neural networks: massively parallel symbolic induction, task decomposition through competition, phoneme discrimination, behavior-based learning, and self-repairing neural networks., Machine learning Congresses, Artificial intelligence Congresses, Neural networks (Computer science) Congresses, Computer science, Artificial intelligence, Microprocessors., Computer architecture., Computation by Abstract Devices, Computer Science, Processor Architectures, Artificial Intelligence (incl. Robotics), Informatik, Informationsverarbeitung, Künstliche Intelligenz, Lerntheorie, Machine, Congresses, Artificial, Neural, Aufsatzsammlung, Maschinelles Lernen |
title |
Machine learning: from theory to applications ; cooperative research at Siemens and MIT |
title_auth |
Machine learning from theory to applications ; cooperative research at Siemens and MIT |
title_full |
Machine learning from theory to applications ; cooperative research at Siemens and MIT S. J. Hanson ... (eds.) |
title_fullStr |
Machine learning from theory to applications ; cooperative research at Siemens and MIT S. J. Hanson ... (eds.) |
title_full_unstemmed |
Machine learning from theory to applications ; cooperative research at Siemens and MIT S. J. Hanson ... (eds.) |
title_in_hierarchy |
661. Machine learning: from theory to applications ; cooperative research at Siemens and MIT (1993) |
title_short |
Machine learning |
title_sort |
machine learning from theory to applications ; cooperative research at siemens and mit |
title_sub |
from theory to applications ; cooperative research at Siemens and MIT |
title_unstemmed |
Machine learning: from theory to applications ; cooperative research at Siemens and MIT |
topic |
Machine learning Congresses, Artificial intelligence Congresses, Neural networks (Computer science) Congresses, Computer science, Artificial intelligence, Microprocessors., Computer architecture., Computation by Abstract Devices, Computer Science, Processor Architectures, Artificial Intelligence (incl. Robotics), Informatik, Informationsverarbeitung, Künstliche Intelligenz, Lerntheorie, Machine, Congresses, Artificial, Neural, Aufsatzsammlung, Maschinelles Lernen |
topic_facet |
Machine learning, Artificial intelligence, Neural networks (Computer science), Computer science, Microprocessors., Computer architecture., Computation by Abstract Devices, Computer Science, Processor Architectures, Artificial Intelligence (incl. Robotics), Informatik, Informationsverarbeitung, Künstliche Intelligenz, Lerntheorie, Congresses, Aufsatzsammlung, Maschinelles Lernen, Machine, Artificial, Neural |
url |
http://www.springerlink.com/content/ul47l844n871, http://www.springerlink.de/openurl.asp?genre=book&isbn=978-3-540-56483-6, http://dx.doi.org/10.1007/3-540-56483-7, https://doi.org/10.1007/3-540-56483-7, https://zbmath.org/?q=an:0825.00048 |
work_keys_str_mv |
AT hansonstephenjose machinelearningfromtheorytoapplicationscooperativeresearchatsiemensandmit |