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ORCIDTai Le Quy
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2020 – today
- 2024
[b1]Tai Le Quy
:
Fairness-aware Machine Learning in Educational Data Mining. University of Hanover, Germany, 2024- [i8]Sribala Vidyadhari Chinta, Zichong Wang, Zhipeng Yin, Nhat Hoang, Matthew Gonzalez, Tai Le Quy, Wenbin Zhang:
FairAIED: Navigating Fairness, Bias, and Ethics in Educational AI Applications. CoRR abs/2407.18745 (2024) - 2023
- [c7]Tai Le Quy, Gunnar Friege, Eirini Ntoutsi:
Multi-fair Capacitated Students-Topics Grouping Problem. PAKDD (1) 2023: 507-519 - [i7]Tai Le Quy, Gunnar Friege, Eirini Ntoutsi:
A review of clustering models in educational data science towards fairness-aware learning. CoRR abs/2301.03421 (2023) - 2022
- [j2]Huyen Giang Thi Thu, Thuy Nguyen Thanh, Tai Le Quy:
Dynamic Sliding Window and Neighborhood LSTM-Based Model for Stock Price Prediction. SN Comput. Sci. 3(3): 256 (2022) - [j1]Tai Le Quy, Arjun Roy, Vasileios Iosifidis, Wenbin Zhang, Eirini Ntoutsi:
A survey on datasets for fairness-aware machine learning. WIREs Data Mining Knowl. Discov. 12(3) (2022) - [c6]Tai Le Quy, Thi Huyen Nguyen, Gunnar Friege, Eirini Ntoutsi:
Evaluation of Group Fairness Measures in Student Performance Prediction Problems. PKDD/ECML Workshops (1) 2022: 119-136 - [i6]Xuejiao Tang, Tai Le Quy, Eirini Ntoutsi, Kea Turner, Vasile Palade, Israat Haque, Peng Xu, Chris Brown, Wenbin Zhang:
Attention Mechanism based Cognition-level Scene Understanding. CoRR abs/2204.08027 (2022) - [i5]Tai Le Quy, Gunnar Friege, Eirini Ntoutsi:
Multiple Fairness and Cardinality constraints for Students-Topics Grouping Problem. CoRR abs/2206.09895 (2022) - [i4]Tai Le Quy, Thi Huyen Nguyen, Gunnar Friege, Eirini Ntoutsi:
Evaluation of group fairness measures in student performance prediction problems. CoRR abs/2208.10625 (2022) - 2021
- [c5]Huyen Giang Thi Thu, Thuy Nguyen Thanh, Tai Le Quy:
A Neighborhood Deep Neural Network Model using Sliding Window for Stock Price Prediction. BigComp 2021: 69-74 - [c4]Tai Le Quy, Eirini Ntoutsi:
Towards fair, explainable and actionable clustering for learning analytics. EDM 2021 - [c3]Tai Le Quy, Arjun Roy, Gunnar Friege, Eirini Ntoutsi:
Fair-Capacitated Clustering. EDM 2021 - [i3]Tai Le Quy, Sergej Zerr, Eirini Ntoutsi, Wolfgang Nejdl:
Data augmentation for dealing with low sampling rates in NILM. CoRR abs/2104.02055 (2021) - [i2]Tai Le Quy, Arjun Roy, Gunnar Friege, Eirini Ntoutsi:
Fair-Capacitated Clustering. CoRR abs/2104.12116 (2021) - [i1]Tai Le Quy, Arjun Roy, Vasileios Iosifidis, Eirini Ntoutsi:
A survey on datasets for fairness-aware machine learning. CoRR abs/2110.00530 (2021) - 2020
- [c2]Bahman Askari, Tai Le Quy, Eirini Ntoutsi:
Taxi Demand Prediction using an LSTM-Based Deep Sequence Model and Points of Interest. COMPSAC 2020: 1719-1724
2010 – 2019
- 2019
- [c1]Tai Le Quy, Wolfgang Nejdl, Myra Spiliopoulou, Eirini Ntoutsi:
A Neighborhood-Augmented LSTM Model for Taxi-Passenger Demand Prediction. MASTER@PKDD/ECML 2019: 100-116
Coauthor Index
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