Federated deep active learning for attention-based transaction classification-Reference-Cited by-同舟云学术

Federated deep active learning for attention-based transaction classification

Published:2023-01-23 Issue:8 Volume:53 Page:8631-8643
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Ahmed Usman,Lin Jerry Chun-Wei^ORCID,Fournier-Viger Philippe

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

https://link.springer.com/content/pdf/10.1007/s10489-022-04388-1.pdf

Reference32 articles.

1. Liu Y, Yu J, Xu L, Wang L, Yang J (2022) Sissos: intervention of tabular data and its applications. Appl Intell 52(1):1044–1058

2. Ahmed U, Srivastava G, Lin JC-W (2021) A federated learning approach to frequent itemset mining in cyber-physical systems. J Netw Syst Manag 29(4):1–17

3. Agrawal R, Srikant R (1994) Fast algorithms for mining association rules. In: Proceeding of the 20th international conference on very large databases, vol 1215, pp 487–499

4. Fournier-Viger P, Lin JC-W, Kiran RU, Koh YS, Thomas R (2017) A survey of sequential pattern mining. Data Sci Pattern Recognit 1(1):54–77

5. Mannila H, Toivonen H, Verkamo AI (1997) Discovery of frequent episodes in event sequences. Data Min Knowl Disc 1(3):259–289

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Exploration on Automatic Recommendation System for Video Background Music Based on Machine Learning;Lecture Notes on Data Engineering and Communications Technologies;2024

2. Cognitive Health Assessment of Decentralized Smart home Activities using Federated Learning;2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing Workshops (CCGridW);2023-05