Boosting over non-deterministic ZDDs

Takahiro Fujita, Kohei Hatano, Eiji Takimoto

研究成果: 著書/レポートタイプへの貢献会議での発言

1 引用 (Scopus)

抄録

We propose a new approach to large-scale machine learning, learning over compressed data: First compress the training data somehow and then employ various machine learning algorithms on the compressed data, with the hope that the computation time is significantly reduced when the training data is well compressed. As the first step, we consider a variant of the Zero-Suppressed Binary Decision Diagram (ZDD) as the data structure for representing the training data, which is a generalization of the ZDD by incorporating non-determinism. For the learning algorithm to be employed, we consider boosting algorithm called AdaBoost* and its precursor AdaBoost. In this work, we give efficient implementations of the boosting algorithms whose running times (per iteration) are linear in the size of the given ZDD.

元の言語英語
ホスト出版物のタイトルWALCOM
ホスト出版物のサブタイトルAlgorithms and Computation - 12th International Conference, WALCOM 2018, Proceedings
編集者M. Sohel Rahman, Wing-Kin Sung, Ryuhei Uehara
出版者Springer Verlag
ページ195-206
ページ数12
ISBN(印刷物)9783319751719
DOI
出版物ステータス出版済み - 1 1 2018
イベント12th International Conference and Workshop on Algorithms and Computation, WALCOM 2018 - Dhaka, バングラデシュ
継続期間: 3 3 20183 5 2018

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)
10755 LNCS
ISSN(印刷物)0302-9743
ISSN(電子版)1611-3349

その他

その他12th International Conference and Workshop on Algorithms and Computation, WALCOM 2018
バングラデシュ
Dhaka
期間3/3/183/5/18

Fingerprint

Binary decision diagrams
Boosting
Adaptive boosting
Decision Diagrams
Learning algorithms
Learning systems
AdaBoost
Binary
Learning Algorithm
Machine Learning
Zero
Data structures
Nondeterminism
Efficient Implementation
Precursor
Data Structures
Iteration
Training

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

これを引用

Fujita, T., Hatano, K., & Takimoto, E. (2018). Boosting over non-deterministic ZDDs. : M. S. Rahman, W-K. Sung, & R. Uehara (版), WALCOM: Algorithms and Computation - 12th International Conference, WALCOM 2018, Proceedings (pp. 195-206). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻数 10755 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-75172-6_17

Boosting over non-deterministic ZDDs. / Fujita, Takahiro; Hatano, Kohei; Takimoto, Eiji.

WALCOM: Algorithms and Computation - 12th International Conference, WALCOM 2018, Proceedings. 版 / M. Sohel Rahman; Wing-Kin Sung; Ryuhei Uehara. Springer Verlag, 2018. p. 195-206 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻 10755 LNCS).

研究成果: 著書/レポートタイプへの貢献会議での発言

Fujita, T, Hatano, K & Takimoto, E 2018, Boosting over non-deterministic ZDDs. : MS Rahman, W-K Sung & R Uehara (版), WALCOM: Algorithms and Computation - 12th International Conference, WALCOM 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 巻. 10755 LNCS, Springer Verlag, pp. 195-206, 12th International Conference and Workshop on Algorithms and Computation, WALCOM 2018, Dhaka, バングラデシュ, 3/3/18. https://doi.org/10.1007/978-3-319-75172-6_17
Fujita T, Hatano K, Takimoto E. Boosting over non-deterministic ZDDs. : Rahman MS, Sung W-K, Uehara R, 編集者, WALCOM: Algorithms and Computation - 12th International Conference, WALCOM 2018, Proceedings. Springer Verlag. 2018. p. 195-206. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-75172-6_17
Fujita, Takahiro ; Hatano, Kohei ; Takimoto, Eiji. / Boosting over non-deterministic ZDDs. WALCOM: Algorithms and Computation - 12th International Conference, WALCOM 2018, Proceedings. 編集者 / M. Sohel Rahman ; Wing-Kin Sung ; Ryuhei Uehara. Springer Verlag, 2018. pp. 195-206 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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