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Discovery Science

20th International Conference, DS 2017, Kyoto, Japan, October 15–17, 2017, Proceedings

  • Conference proceedings
  • © 2017

Overview

Editors:
  1. Akihiro Yamamoto

    1. Kyoto University, Kyoto, Japan

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  2. Takuya Kida

    1. Hokkaido University, Sapporo, Japan

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  3. Takeaki Uno

    1. National Institute of Informatics, Tokyo, Japan

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  4. Tetsuji Kuboyama

    1. Gakushuin University, Tokyo, Japan

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10558)

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

Included in the following conference series:

Conference proceedings info: DS 2017.

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Table of contents (24 papers)

  1. Front Matter

    Pages I-XV
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  2. Online Learning

    1. Front Matter

      Pages 1-1
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    2. Context-Based Abrupt Change Detection and Adaptation for Categorical Data Streams

      • Sarah D’Ettorre, Herna L. Viktor, Eric Paquet
      Pages 3-17

    3. A New Adaptive Learning Algorithm and Its Application to Online Malware Detection

      • Ngoc Anh Huynh, Wee Keong Ng, Kanishka Ariyapala
      Pages 18-32

    4. Real-Time Validation of Retail Gasoline Prices

      • Mondelle Simeon, Howard J. Hamilton
      Pages 33-47

  3. Regression

    1. Front Matter

      Pages 49-49
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    2. General Meta-Model Framework for Surrogate-Based Numerical Optimization

      • Žiga Lukšič, Jovan Tanevski, Sašo Džeroski, Ljupčo Todorovski
      Pages 51-66

    3. Evaluation of Different Heuristics for Accommodating Asymmetric Loss Functions in Regression

      • Andrei Tolstikov, Frederik Janssen, Johannes Fürnkranz
      Pages 67-81

    4. Differentially Private Empirical Risk Minimization with Input Perturbation

      • Kazuto Fukuchi, Quang Khai Tran, Jun Sakuma
      Pages 82-90

  4. Label Classification

    1. Front Matter

      Pages 91-91
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    2. On a New Competence Measure Applied to the Dynamic Selection of Classifiers Ensemble

      • Marek Kurzynski, Pawel Trajdos
      Pages 93-107

    3. Multi-label Classification Using Random Label Subset Selections

      • Martin Breskvar, Dragi Kocev, Sašo Džeroski
      Pages 108-115

    4. Option Predictive Clustering Trees for Hierarchical Multi-label Classification

      • Tomaž Stepišnik Perdih, Aljaž Osojnik, Sašo Džeroski, Dragi Kocev
      Pages 116-123

  5. Deep Learning

    1. Front Matter

      Pages 125-125
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    2. Re-training Deep Neural Networks to Facilitate Boolean Concept Extraction

      • Camila González, Eneldo Loza Mencía, Johannes Fürnkranz
      Pages 127-143

    3. An In-Depth Experimental Comparison of RNTNs and CNNs for Sentence Modeling

      • Zahra Ahmadi, Marcin Skowron, Aleksandrs Stier, Stefan Kramer
      Pages 144-152

  6. Feature Selection

    1. Front Matter

      Pages 153-153
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    2. Improving Classification Accuracy by Means of the Sliding Window Method in Consistency-Based Feature Selection

      • Adrian Pino Angulo, Kilho Shin
      Pages 155-170

    3. Feature Ranking for Multi-target Regression with Tree Ensemble Methods

      • Matej Petković, Sašo Džeroski, Dragi Kocev
      Pages 171-185

  7. Recommendation System

    1. Front Matter

      Pages 187-187
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Other volumes

  1. Discovery Science

Keywords

About this book

This book constitutes the proceedings of the 20th International Conference on Discovery Science, DS 2017, held in Kyoto, Japan, in October 2017, co-located with the International Conference on Algorithmic Learning Theory, ALT 2017.

The 18 revised full papers presented together with 6 short papers and 2 invited talks in this volume were carefully reviewed and selected from 42 submissions. The scope of the conference includes the development and analysis of methods for discovering scientific knowledge, coming from machine learning, data mining, intelligent data analysis, big data analysis as well as their application in various scientific domains. The papers are organized in topical sections on machine learning: online learning, regression, label classification, deep learning, feature selection, recommendation system; and knowledge discovery: recommendation system, community detection, pattern mining, misc.

Editors and Affiliations

  • Kyoto University, Kyoto, Japan

    Akihiro Yamamoto

  • Hokkaido University, Sapporo, Japan

    Takuya Kida

  • National Institute of Informatics, Tokyo, Japan

    Takeaki Uno

  • Gakushuin University, Tokyo, Japan

    Tetsuji Kuboyama

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