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Journal Articles
- 2023
[j5]Tadahiro Taniguchi
, Yuto Yoshida, Yuta Matsui, Nguyen Le Hoang, Akira Taniguchi, Yoshinobu Hagiwara:
Emergent communication through Metropolis-Hastings naming game with deep generative models. Adv. Robotics 37(19): 1266-1282 (2023)- [j4]Nguyen Le Hoang, Tadahiro Taniguchi, Yoshinobu Hagiwara, Akira Taniguchi:
Emergent communication of multimodal deep generative models based on Metropolis-Hastings naming game. Frontiers Robotics AI 10 (2023) - [j3]Nguyen Le Hoang, Tran Khanh Dang:
Enhancing Big Data Conversion Validation with Alpha-Lightweight Coreset. SN Comput. Sci. 4(6): 799 (2023) - 2021
- [j2]Tran Khanh Dang, Manh Huy Ta, Ly Hoang Dang, Nguyen Le Hoang:
An Elastic Data Conversion Framework: A Case Study for MySQL and MongoDB. SN Comput. Sci. 2(4): 325 (2021) - 2020
- [j1]Nguyen Le Hoang, Le Hong Trang, Tran Khanh Dang:
A Comparative Study of the Some Methods Used in Constructing Coresets for Clustering Large Datasets. SN Comput. Sci. 1(4): 215 (2020)
Conference and Workshop Papers
- 2024
- [c7]Nguyen Le Hoang, Yuta Matsui, Yoshinobu Hagiwara, Akira Taniguchi, Tadahiro Taniguchi:
Compositionality and Generalization in Emergent Communication Using Metropolis-Hastings Naming Game. ICDL 2024: 1-7 - 2022
- [c6]Nguyen Le Hoang, Tran Khanh Dang, Thai San Dang:
Implement the Data Conversion System by Using α-Lightweight Coreset for Validation Process. FDSE (CCIS Volume) 2022: 103-118 - [c5]Nguyen Le Hoang, Tran Khanh Dang:
Alpha Lightweight Coreset for k-Means Clustering. IMCOM 2022: 1-8 - 2021
- [c4]Tran Khanh Dang, Manh Huy Ta, Nguyen Le Hoang:
Intermediate Data Format for the Elastic Data Conversion Framework. IMCOM 2021: 1-5 - 2020
- [c3]Tran Khanh Dang, Manh Huy Ta, Nguyen Le Hoang:
An Elastic Data Conversion Framework for Data Integration System. FDSE (CCIS Volume) 2020: 35-50 - [c2]Le Hong Trang, Nguyen Le Hoang, Tran Khanh Dang:
A Farthest First Traversal based Sampling Algorithm for k-clustering. IMCOM 2020: 1-6 - 2019
- [c1]Nguyen Le Hoang, Tran Khanh Dang, Le Hong Trang:
A Comparative Study of the Use of Coresets for Clustering Large Datasets. FDSE 2019: 45-55
Coauthor Index
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