A compression-based dissimilarity measure for multi-task clustering

Nguyen Huy Thach, Hao Shao, Bin Tong, Einoshin Suzuki

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

6 被引用数 (Scopus)

抄録

Virtually all existing multi-task learning methods for string data require either domain specific knowledge to extract feature representations or a careful setting of many input parameters. In this work, we propose a feature-free and parameter-light multi-task clustering algorithm for string data. To transfer knowledge between different domains, a novel dictionary-based compression dissimilarity measure is proposed. Experimental results with extensive comparisons demonstrate the generality and the effectiveness of our proposal.

本文言語英語
ホスト出版物のタイトルFoundations of Intelligent Systems - 19th International Symposium, ISMIS 2011, Proceedings
ページ123-132
ページ数10
DOI
出版ステータス出版済み - 7 14 2011
イベント19th International Symposium on Methodologies for Intelligent Systems, ISMIS 2011 - Warsaw, ポーランド
継続期間: 6 28 20116 30 2011

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
6804 LNAI
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

その他

その他19th International Symposium on Methodologies for Intelligent Systems, ISMIS 2011
Countryポーランド
CityWarsaw
Period6/28/116/30/11

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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