Federated Erasable-Itemset Mining with Quasi-Erasable Itemsets

Author:

Hong Tzung-Pei,Kuo Meng-Jui,Chen Chun-Hao,Li Katherine Shu-Min

Publisher

Springer Nature Singapore

Reference13 articles.

1. Deng, Z.H., Fang, G., Wang, Z., Xu, X.: Mining erasable itemsets. In: The 2009 International Conference on Machine Learning and Cybernetics, vol. 1, pp. 67–73 (2009)

2. Hong, T.P., Tao, Y.H., Wang, C.Y.: A new incremental data mining algorithm using pre-large itemsets. J. Intell. Data Anal. 5(2), 111–129 (2001)

3. Vo, B., Le, T., Hong, T.-P., Le, B.: An effective approach for maintenance of pre-large-based frequent-itemset lattice in incremental mining. Appl. Intell. 41(3), 759–775 (2014). https://doi.org/10.1007/s10489-014-0551-z

4. Li, T., Sahu, A.K., Talwalkar, A., Smith, V.: Federated learning challenges, methods, and future directions. IEEE Signal Process. Mag., 50–60 (2020)

5. Mcmahan, E.M., Ramage, D., Hampson, S., Arcas, B.A.Y.: Communication-efficient learning of deep networks from decentralized data. Art. Intell. Stat. 54, 1273–1282 (2017)

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