Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2014, Nancy, France, September 15-19, 2014. Proceedings, Part III | SpringerLink
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Machine Learning and Knowledge Discovery in Databases

European Conference, ECML PKDD 2014, Nancy, France, September 15-19, 2014. Proceedings, Part III

  • Conference proceedings
  • © 2014

Overview

Editors:
  1. Toon Calders

    1. Faculty of Applied Sciences, Department of Computer and Decision Engineering, Université Libre de Bruxelles, Brussels, Belgium

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  2. Floriana Esposito

    1. Dipartimento di Informatica, Università degli Studi “Aldo Moro”, Bari, Italy

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    You can also search for this editor in PubMed   Google Scholar

  3. Eyke Hüllermeier

    1. Department of Computer Science, Universität Paderborn, Paderborn, Germany

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    You can also search for this editor in PubMed   Google Scholar

  4. Rosa Meo

    1. Dipartimento di Informatica,, Università degli Studi di Torino, Torino, Italy

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 8726)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: ECML PKDD 2014.

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About this book

This three-volume set LNAI 8724, 8725 and 8726 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2014, held in Nancy, France, in September 2014. The 115 revised research papers presented together with 13 demo track papers, 10 nectar track papers, 8 PhD track papers, and 9 invited talks were carefully reviewed and selected from 550 submissions. The papers cover the latest high-quality interdisciplinary research results in all areas related to machine learning and knowledge discovery in databases.

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Table of contents (50 papers)

  1. Front Matter

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  2. Main Track Contributions

    1. FLIP: Active Learning for Relational Network Classification

      • Tanwistha Saha, Huzefa Rangwala, Carlotta Domeniconi
      Pages 1-18

    2. Clustering via Mode Seeking by Direct Estimation of the Gradient of a Log-Density

      • Hiroaki Sasaki, Aapo Hyvärinen, Masashi Sugiyama
      Pages 19-34

    3. Local Policy Search in a Convex Space and Conservative Policy Iteration as Boosted Policy Search

      • Bruno Scherrer, Matthieu Geist
      Pages 35-50

    4. Code You Are Happy to Paste: An Algorithmic Dictionary of Exponential Families

      • Olivier Schwander
      Pages 51-65

    5. Statistical Hypothesis Testing in Positive Unlabelled Data

      • Konstantinos Sechidis, Borja Calvo, Gavin Brown
      Pages 66-81

    6. Students, Teachers, Exams and MOOCs: Predicting and Optimizing Attainment in Web-Based Education Using a Probabilistic Graphical Model

      • Bar Shalem, Yoram Bachrach, John Guiver, Christopher M. Bishop
      Pages 82-97

    7. Gaussian Process Multi-task Learning Using Joint Feature Selection

      • P. K. Srijith, Shirish Shevade
      Pages 98-113

    8. Separating Rule Refinement and Rule Selection Heuristics in Inductive Rule Learning

      • Julius Stecher, Frederik Janssen, Johannes Fürnkranz
      Pages 114-129

    9. Scalable Information Flow Mining in Networks

      • Karthik Subbian, Chidananda Sridhar, Charu C. Aggarwal, Jaideep Srivastava
      Pages 130-146

    10. Link Prediction in Multi-modal Social Networks

      • Panagiotis Symeonidis, Christos Perentis
      Pages 147-162

    11. Faster Way to Agony

      • Nikolaj Tatti
      Pages 163-178

    12. Speeding Up Recovery from Concept Drifts

      • Silas Garrido Teixeira de Carvalho Santos, Paulo Mauricio Gonçalves Júnior, Geyson Daniel dos Santos Silva, Roberto Souto Maior de Barros
      Pages 179-194

    13. Training Restricted Boltzmann Machines with Overlapping Partitions

      • Hasari Tosun, John W. Sheppard
      Pages 195-208

    14. Integer Bayesian Network Classifiers

      • Sebastian Tschiatschek, Karin Paul, Franz Pernkopf
      Pages 209-224

    15. Multi-target Regression via Random Linear Target Combinations

      • Grigorios Tsoumakas, Eleftherios Spyromitros-Xioufis, Aikaterini Vrekou, Ioannis Vlahavas
      Pages 225-240

    16. Ratio-Based Multiple Kernel Clustering

      • Grigorios Tzortzis, Aristidis Likas
      Pages 241-257

    17. Evidence-Based Clustering for Scalable Inference in Markov Logic

      • Deepak Venugopal, Vibhav Gogate
      Pages 258-273

    18. On Learning Matrices with Orthogonal Columns or Disjoint Supports

      • Kevin Vervier, Pierre Mahé, Alexandre D’Aspremont, Jean-Baptiste Veyrieras, Jean-Philippe Vert
      Pages 274-289

    19. Scalable Moment-Based Inference for Latent Dirichlet Allocation

      • Chi Wang, Xueqing Liu, Yanglei Song, Jiawei Han
      Pages 290-305
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Other volumes

  1. Machine Learning and Knowledge Discovery in Databases

  2. Machine Learning and Knowledge Discovery in Databases

  3. Machine Learning and Knowledge Discovery in Databases

Editors and Affiliations

  • Faculty of Applied Sciences, Department of Computer and Decision Engineering, Université Libre de Bruxelles, Brussels, Belgium

    Toon Calders

  • Dipartimento di Informatica, Università degli Studi “Aldo Moro”, Bari, Italy

    Floriana Esposito

  • Department of Computer Science, Universität Paderborn, Paderborn, Germany

    Eyke Hüllermeier

  • Dipartimento di Informatica,, Università degli Studi di Torino, Torino, Italy

    Rosa Meo

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