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The Resource Machine learning, ECML-93 : European Conference on Machine Learning, Vienna, Australia, April 5-7, 1993 : proceedings, Pavel B. Brazdil, ed

Machine learning, ECML-93 : European Conference on Machine Learning, Vienna, Australia, April 5-7, 1993 : proceedings, Pavel B. Brazdil, ed

Creator
Contributor
Summary
"This volume contains the proceedings of the Eurpoean Conference on Machine Learning (ECML-93), continuing the tradition of the five earlier EWSLs (European Working Sessions on Learning). The aim of these conferences is to provide a platform for presenting the latest results in the area of machine learning. The ECML-93 programme included invited talks, selected papers, and the presentation of ongoing work in poster sessions. The programme was completed by several workshops on specific topics. The volume contains papers related to all these activities. The first chapter of the proceedings contains two invited papers, one by Ross Quinlan and one by Stephen Muggleton on inductive logic programming. The second chapter contains 18 scientific papers accepted for the main sessions of the conference. The third chapter contains 18 shorter position papers. The final chapter includes three overview papers related to the ECML-93 workshops."--PUBLISHER'S WEBSITE
Language
eng
Work
Publication
Extent
xii, 469 pages
Contents
  • Decision Tree Pruning as a Search in the State Space / F. Esposito, D. Malerba and G. Semeraro. Controlled Redundancy in Incremental Rule Learning / L. Torgo. Getting Order Independence in Incremental Learning / A. Cornuejols. Feature Selection Using Rough Sets Theory / M. Modrzejewski -- Learning in Dynamic Environments. Effective Learning in Dynamic Environments by Explicit Context Tracking / G. Widmer and M. Kubat. COBBIT -- A Control Procedure for COBWEB in the Presence of Concept Drift / F. Kilander and C.G. Jansson -- Genetic Algorithms. Genetic Algorithms for Protein Tertiary Structure Prediction / S. Schulze-Kremer. SIA: A Supervised Inductive Algorithm with Genetic Search for Learning Attributes based Concepts / G. Venturini. SAMIA: A Bottom-up Learning Method Using a Simulated Annealing Algorithm / P. Brezellec and H. Soldano -- Inductive Logic Programming. Predicate Invention in ILP -- an Overview / I. Stahl
  • Functional Inductive Logic Programming with Queries to the User / F. Bergadano and D. Gunetti. A Note on Refinement Operators / T. Niblett. An Iterative and Bottom-up Procedure for Proving-by-Example / M. Hagiya -- Learnability. Learnability of Constrained Logic Programs / S. Dzeroski, S. Muggleton and S. Russell. Complexity Dimensions and Learnability / S.-H. Nienhuys-Cheng and M. Polman. Can Complexity Theory Benefit from Learning Theory? / T. Hegedus -- Learning from Time Dependent Data. Learning Domain Theories Using Abstract Background Knowledge / P. Clark and S. Matwin. Discovering Patterns in EEG-Signals: Comparative Study of a Few Methods / M. Kubat, D. Flotzinger and G. Pfurtscheller. Learning to Control Dynamic Systems with Automatic Quantization / C.X. Ling and R. Buchal -- Inductive Learning and Applications. Refinement of Rule Sets with JoJo / D. Fensel and M. Wiese. Rule Combination in Inductive Learning / L. Torgo
  • Using Heuristics to Speed up Induction on Continuous-Valued Attributes / G. Seidelmann. Integrating Models of Knowledge and Machine Learning / J.-G. Ganascia, J. Thomas and P. Laublet. Exploiting Context when Learning to Classify / P.D. Turney. IDDD: An Inductive, Domain Dependent Decision Algorithm / L. Gaga, V. Moustakis, G. Charissis and S. Orphanoudakis. An Application of Machine Learning in the Domain of Loan Analysis / J. Ferreira, J. Correia, T. Jamet and E. Costa -- Neural Network Learning. Extraction of Knowledge from Data using Constrained Neural Networks / R. Kane, I. Tchoumatchenko and M. Milgram. Integrated Learning Architectures / E. Plaza, A. Aamodt, A. Ram, W. van de Velde and M. van Someren. An Overview of Evolutionary Computation / W.M. Spears, K.A. De Jong, T. Back, D.B. Fogel and H. de Garis. ML Techniques and Text Analysis / P. Adriaans
Isbn
9783540566021
Instance
Label
Machine learning, ECML-93 : European Conference on Machine Learning, Vienna, Australia, April 5-7, 1993 : proceedings
Title
Machine learning, ECML-93
Title remainder
European Conference on Machine Learning, Vienna, Australia, April 5-7, 1993 : proceedings
Statement of responsibility
Pavel B. Brazdil, ed
Creator
Contributor
Subject
Genre
Language
eng
Summary
"This volume contains the proceedings of the Eurpoean Conference on Machine Learning (ECML-93), continuing the tradition of the five earlier EWSLs (European Working Sessions on Learning). The aim of these conferences is to provide a platform for presenting the latest results in the area of machine learning. The ECML-93 programme included invited talks, selected papers, and the presentation of ongoing work in poster sessions. The programme was completed by several workshops on specific topics. The volume contains papers related to all these activities. The first chapter of the proceedings contains two invited papers, one by Ross Quinlan and one by Stephen Muggleton on inductive logic programming. The second chapter contains 18 scientific papers accepted for the main sessions of the conference. The third chapter contains 18 shorter position papers. The final chapter includes three overview papers related to the ECML-93 workshops."--PUBLISHER'S WEBSITE
Member of
Cataloging source
DLC
Illustrations
illustrations
Index
index present
LC call number
  • Q325.5
  • QA75.5
LC item number
  • .E85 1993
  • .L43 v. 667
Literary form
non fiction
http://bibfra.me/vocab/lite/meetingDate
1993
http://bibfra.me/vocab/lite/meetingName
European Conference on Machine Learning
Nature of contents
bibliography
http://library.link/vocab/relatedWorkOrContributorDate
1945-
http://library.link/vocab/relatedWorkOrContributorName
Brazdil, Pavel B.
Series statement
  • Lecture notes in computer science
  • Lecture notes in artificial intelligence
Series volume
667.
http://library.link/vocab/subjectName
  • Machine learning
  • Learning, Psychology of
  • Induction (Logic)
  • logique induction
  • induction
  • algorithme génétique
  • apprentissage
  • programmation en logique
  • apprentissage machine
  • Apprentissage automatique
  • Apprentissage, Psychologie de l'
  • Induction (Logique)
  • Induction (Logic)
  • Learning, Psychology of
  • Machine learning
  • Machine-learning
  • Leerpsychologie
  • Apprentissage automatique
  • Psychologie de l'apprentissage
  • Induction (logique)
Label
Machine learning, ECML-93 : European Conference on Machine Learning, Vienna, Australia, April 5-7, 1993 : proceedings, Pavel B. Brazdil, ed
Instantiates
Publication
Bibliography note
Includes bibliographical references and index
Carrier category
volume
Carrier category code
  • nc
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Decision Tree Pruning as a Search in the State Space / F. Esposito, D. Malerba and G. Semeraro. Controlled Redundancy in Incremental Rule Learning / L. Torgo. Getting Order Independence in Incremental Learning / A. Cornuejols. Feature Selection Using Rough Sets Theory / M. Modrzejewski -- Learning in Dynamic Environments. Effective Learning in Dynamic Environments by Explicit Context Tracking / G. Widmer and M. Kubat. COBBIT -- A Control Procedure for COBWEB in the Presence of Concept Drift / F. Kilander and C.G. Jansson -- Genetic Algorithms. Genetic Algorithms for Protein Tertiary Structure Prediction / S. Schulze-Kremer. SIA: A Supervised Inductive Algorithm with Genetic Search for Learning Attributes based Concepts / G. Venturini. SAMIA: A Bottom-up Learning Method Using a Simulated Annealing Algorithm / P. Brezellec and H. Soldano -- Inductive Logic Programming. Predicate Invention in ILP -- an Overview / I. Stahl
  • Functional Inductive Logic Programming with Queries to the User / F. Bergadano and D. Gunetti. A Note on Refinement Operators / T. Niblett. An Iterative and Bottom-up Procedure for Proving-by-Example / M. Hagiya -- Learnability. Learnability of Constrained Logic Programs / S. Dzeroski, S. Muggleton and S. Russell. Complexity Dimensions and Learnability / S.-H. Nienhuys-Cheng and M. Polman. Can Complexity Theory Benefit from Learning Theory? / T. Hegedus -- Learning from Time Dependent Data. Learning Domain Theories Using Abstract Background Knowledge / P. Clark and S. Matwin. Discovering Patterns in EEG-Signals: Comparative Study of a Few Methods / M. Kubat, D. Flotzinger and G. Pfurtscheller. Learning to Control Dynamic Systems with Automatic Quantization / C.X. Ling and R. Buchal -- Inductive Learning and Applications. Refinement of Rule Sets with JoJo / D. Fensel and M. Wiese. Rule Combination in Inductive Learning / L. Torgo
  • Using Heuristics to Speed up Induction on Continuous-Valued Attributes / G. Seidelmann. Integrating Models of Knowledge and Machine Learning / J.-G. Ganascia, J. Thomas and P. Laublet. Exploiting Context when Learning to Classify / P.D. Turney. IDDD: An Inductive, Domain Dependent Decision Algorithm / L. Gaga, V. Moustakis, G. Charissis and S. Orphanoudakis. An Application of Machine Learning in the Domain of Loan Analysis / J. Ferreira, J. Correia, T. Jamet and E. Costa -- Neural Network Learning. Extraction of Knowledge from Data using Constrained Neural Networks / R. Kane, I. Tchoumatchenko and M. Milgram. Integrated Learning Architectures / E. Plaza, A. Aamodt, A. Ram, W. van de Velde and M. van Someren. An Overview of Evolutionary Computation / W.M. Spears, K.A. De Jong, T. Back, D.B. Fogel and H. de Garis. ML Techniques and Text Analysis / P. Adriaans
Dimensions
24 cm.
Extent
xii, 469 pages
Isbn
9783540566021
Isbn Type
(Berlin : alk. paper)
Lccn
93012645
Media category
unmediated
Media MARC source
rdamedia
Media type code
  • n
Other physical details
illustrations
System control number
  • (OCoLC)27726476
  • (OCoLC)ocm27726476
Label
Machine learning, ECML-93 : European Conference on Machine Learning, Vienna, Australia, April 5-7, 1993 : proceedings, Pavel B. Brazdil, ed
Publication
Bibliography note
Includes bibliographical references and index
Carrier category
volume
Carrier category code
  • nc
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • Decision Tree Pruning as a Search in the State Space / F. Esposito, D. Malerba and G. Semeraro. Controlled Redundancy in Incremental Rule Learning / L. Torgo. Getting Order Independence in Incremental Learning / A. Cornuejols. Feature Selection Using Rough Sets Theory / M. Modrzejewski -- Learning in Dynamic Environments. Effective Learning in Dynamic Environments by Explicit Context Tracking / G. Widmer and M. Kubat. COBBIT -- A Control Procedure for COBWEB in the Presence of Concept Drift / F. Kilander and C.G. Jansson -- Genetic Algorithms. Genetic Algorithms for Protein Tertiary Structure Prediction / S. Schulze-Kremer. SIA: A Supervised Inductive Algorithm with Genetic Search for Learning Attributes based Concepts / G. Venturini. SAMIA: A Bottom-up Learning Method Using a Simulated Annealing Algorithm / P. Brezellec and H. Soldano -- Inductive Logic Programming. Predicate Invention in ILP -- an Overview / I. Stahl
  • Functional Inductive Logic Programming with Queries to the User / F. Bergadano and D. Gunetti. A Note on Refinement Operators / T. Niblett. An Iterative and Bottom-up Procedure for Proving-by-Example / M. Hagiya -- Learnability. Learnability of Constrained Logic Programs / S. Dzeroski, S. Muggleton and S. Russell. Complexity Dimensions and Learnability / S.-H. Nienhuys-Cheng and M. Polman. Can Complexity Theory Benefit from Learning Theory? / T. Hegedus -- Learning from Time Dependent Data. Learning Domain Theories Using Abstract Background Knowledge / P. Clark and S. Matwin. Discovering Patterns in EEG-Signals: Comparative Study of a Few Methods / M. Kubat, D. Flotzinger and G. Pfurtscheller. Learning to Control Dynamic Systems with Automatic Quantization / C.X. Ling and R. Buchal -- Inductive Learning and Applications. Refinement of Rule Sets with JoJo / D. Fensel and M. Wiese. Rule Combination in Inductive Learning / L. Torgo
  • Using Heuristics to Speed up Induction on Continuous-Valued Attributes / G. Seidelmann. Integrating Models of Knowledge and Machine Learning / J.-G. Ganascia, J. Thomas and P. Laublet. Exploiting Context when Learning to Classify / P.D. Turney. IDDD: An Inductive, Domain Dependent Decision Algorithm / L. Gaga, V. Moustakis, G. Charissis and S. Orphanoudakis. An Application of Machine Learning in the Domain of Loan Analysis / J. Ferreira, J. Correia, T. Jamet and E. Costa -- Neural Network Learning. Extraction of Knowledge from Data using Constrained Neural Networks / R. Kane, I. Tchoumatchenko and M. Milgram. Integrated Learning Architectures / E. Plaza, A. Aamodt, A. Ram, W. van de Velde and M. van Someren. An Overview of Evolutionary Computation / W.M. Spears, K.A. De Jong, T. Back, D.B. Fogel and H. de Garis. ML Techniques and Text Analysis / P. Adriaans
Dimensions
24 cm.
Extent
xii, 469 pages
Isbn
9783540566021
Isbn Type
(Berlin : alk. paper)
Lccn
93012645
Media category
unmediated
Media MARC source
rdamedia
Media type code
  • n
Other physical details
illustrations
System control number
  • (OCoLC)27726476
  • (OCoLC)ocm27726476

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