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Machine Learning and Knowledge Discovery in Databases

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

  • 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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  3. Eyke Hüllermeier

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

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  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 8724)

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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Keywords

Table of contents (44 papers)

  1. Front Matter

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  2. Main Track Contributions

    1. Classifying a Stream of Infinite Concepts: A Bayesian Non-parametric Approach

      • Seyyed Abbas Hosseini, Hamid R. Rabiee, Hassan Hafez, Ali Soltani-Farani
      Pages 1-16

    2. Fast Nearest Neighbor Search on Large Time-Evolving Graphs

      • Leman Akoglu, Rohit Khandekar, Vibhore Kumar, Srinivasan Parthasarathy, Deepak Rajan, Kun-Lung Wu
      Pages 17-33

    3. Deconstructing Kernel Machines

      • Mohsen Ali, Muhammad Rushdi, Jeffrey Ho
      Pages 34-49

    4. Beyond Blocks: Hyperbolic Community Detection

      • Miguel Araujo, Stephan Günnemann, Gonzalo Mateos, Christos Faloutsos
      Pages 50-65

    5. Concurrent Bandits and Cognitive Radio Networks

      • Orly Avner, Shie Mannor
      Pages 66-81

    6. Kernel Principal Geodesic Analysis

      • Suyash P. Awate, Yen-Yun Yu, Ross T. Whitaker
      Pages 82-98

    7. Attributed Graph Kernels Using the Jensen-Tsallis q-Differences

      • Lu Bai, Luca Rossi, Horst Bunke, Edwin R. Hancock
      Pages 99-114

    8. Sub-sampling for Multi-armed Bandits

      • Akram Baransi, Odalric-Ambrym Maillard, Shie Mannor
      Pages 115-131

    9. Knowledge-Powered Deep Learning for Word Embedding

      • Jiang Bian, Bin Gao, Tie-Yan Liu
      Pages 132-148

    10. Density-Based Subspace Clustering in Heterogeneous Networks

      • Brigitte Boden, Martin Ester, Thomas Seidl
      Pages 149-164

    11. Open Question Answering with Weakly Supervised Embedding Models

      • Antoine Bordes, Jason Weston, Nicolas Usunier
      Pages 165-180

    12. Towards Automatic Feature Construction for Supervised Classification

      • Marc Boullé
      Pages 181-196

    13. Consistency of Losses for Learning from Weak Labels

      • Jesús Cid-Sueiro, Darío García-García, Raúl Santos-Rodríguez
      Pages 197-210

    14. Active Learning for Support Vector Machines with Maximum Model Change

      • Wenbin Cai, Ya Zhang, Siyuan Zhou, Wenquan Wang, Chris Ding, Xiao Gu
      Pages 211-226

    15. Anomaly Detection with Score Functions Based on the Reconstruction Error of the Kernel PCA

      • Laetitia Chapel, Chloé Friguet
      Pages 227-241

    16. Fast Gaussian Pairwise Constrained Spectral Clustering

      • David Chatel, Pascal Denis, Marc Tommasi
      Pages 242-257

    17. A Generative Bayesian Model for Item and User Recommendation in Social Rating Networks with Trust Relationships

      • Gianni Costa, Giuseppe Manco, Riccardo Ortale
      Pages 258-273

    18. Domain Adaptation with Regularized Optimal Transport

      • Nicolas Courty, Rémi Flamary, Devis Tuia
      Pages 274-289

    19. Discriminative Subnetworks with Regularized Spectral Learning for Global-State Network Data

      • Xuan Hong Dang, Ambuj K. Singh, Petko Bogdanov, Hongyuan You, Bayyuan Hsu
      Pages 290-306
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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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