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2020 – today
- 2024
[c14]Chih-Yuan Li, Jun-Ting Wu, Chan Hsu, Ming-Yen Lin, Yihuang Kang:
Understanding eGFR Trajectories and Kidney Function Decline via Large Multimodal Models. MIPR 2024: 667-673- [i11]Chan Hsu, Jun-Ting Wu, Yihuang Kang:
Causal Rule Forest: Toward Interpretable and Precise Treatment Effect Estimation. CoRR abs/2408.15055 (2024) - [i10]I-Ling Cheng, Chan Hsu, Chan-Tung Ku, Pei-Ju Lee, Yihuang Kang:
Subgroup Analysis via Model-based Rule Forest. CoRR abs/2408.15057 (2024) - [i9]Chih-Yuan Li, Jun-Ting Wu, Chan Hsu, Ming-Yen Lin, Yihuang Kang:
Understanding eGFR Trajectories and Kidney Function Decline via Large Multimodal Models. CoRR abs/2409.02530 (2024) - 2023
- [c13]Chan Hsu, Chan-Tung Ku, Yuwen Wang, Minchen Hsieh, Jun-Ting Wu, Yunhsiang Hsieh, PoFeng Chang, Yimin Lu, Yihuang Kang:
A Teacher-Student Knowledge Distillation Framework for Enhanced Detection of Anomalous User Activity. IRI 2023: 20-21 - [c12]Chan Hsu, Wei-Chun Huang, Jun-Ting Wu, Chih-Yuan Li, Yihuang Kang:
Toward Transparent Sequence Models with Model-Based Tree Markov Model. MIPR 2023: 1-6 - [i8]Chan Hsu, Wei-Chun Huang, Jun-Ting Wu, Chih-Yuan Li, Yihuang Kang:
Toward Transparent Sequence Models with Model-Based Tree Markov Model. CoRR abs/2307.15367 (2023) - 2022
- [j4]Shih-Yi Chien
, Shiau-Fang Chao, Yihuang Kang, Chan Hsu, Meng-Hsuan Yu, Chan-Tung Ku:
Understanding Predictive Factors of Dementia for Older Adults: A Machine Learning Approach for Modeling Dementia Influencers. Int. J. Hum. Comput. Stud. 165: 102834 (2022) - [c11]Chan Hsu, Ching-Chih Tsao, Yu-Liang Weng, Cheng-Yi Tang, Yu-Wen Chang, Yihuang Kang, Shih-Yi Chien:
A Machine Learning Approach to Model HRI Research Trends in 2010~2021. HRI 2022: 812-815 - 2021
- [j3]Ming-Yen Lin, Jia-Sin Liu, Tzu-Yang Huang, Ping-Hsun Wu, Yi-Wen Chiu, Yihuang Kang, Chih-Cheng Hsu, Shang-Jyh Hwang, Hsing Paul Luh:
Data Analysis of the Risks of Type 2 Diabetes Mellitus Complications before Death Using a Data-Driven Modelling Approach: Methodologies and Challenges in Prolonged Diseases. Inf. 12(8): 326 (2021) - [j2]Yihuang Kang, Sheng-Tai Huang, Pinghsung Wu:
Detection of Drug-Drug and Drug-Disease Interactions Inducing Acute Kidney Injury Using Deep Rule Forests. SN Comput. Sci. 2(4): 299 (2021) - [c10]Yihuang Kang, Yi-Wen Chiu, Ming-Yen Lin, Fang-Yi Su, Sheng-Tai Huang:
Towards Model-informed Precision Dosing with Expert-in-the-loop Machine Learning. IRI 2021: 342-347 - [i7]Yihuang Kang, Yi-Wen Chiu, Ming-Yen Lin, Fang-Yi Su, Sheng-Tai Huang:
Towards Model-informed Precision Dosing with Expert-in-the-loop Machine Learning. CoRR abs/2106.14384 (2021) - 2020
- [c9]Bowen Kuo, Yihuang Kang, Pinghsung Wu, Sheng-Tai Huang, Yajie Huang:
Discovering Drug-Drug and Drug-Disease Interactions Inducing Acute Kidney Injury Using Deep Rule Forests. IRI 2020: 385-390 - [c8]Sheng-Tai Huang, Yihuang Kang, Shao-Min Hung, Bowen Kuo, I-Ling Cheng:
Topic Diffusion Discovery based on Deep Non-negative Autoencoder. IRI 2020: 405-408 - [i6]Bowen Kuo, Yihuang Kang, Pinghsung Wu, Sheng-Tai Huang, Yajie Huang:
Discovering Drug-Drug and Drug-Disease Interactions Inducing Acute Kidney Injury Using Deep Rule Forests. CoRR abs/2007.02103 (2020) - [i5]Sheng-Tai Huang, Yihuang Kang, Shao-Min Hung, Bowen Kuo, I-Ling Cheng:
Topic Diffusion Discovery Based on Deep Non-negative Autoencoder. CoRR abs/2010.03710 (2020)
2010 – 2019
- 2019
- [c7]Pei-Ju Lee, Yen-Hsien Lee, Yihuang Kang, Ching-Ping Chao:
A Medical Decision Support System Using Text Mining to Compare Electronic Medical Records. HCI (24) 2019: 199-208 - [c6]Yihuang Kang, I-Ling Cheng, Wenjui Mao, Bowen Kuo, Pei-Ju Lee:
Towards Interpretable Deep Extreme Multi-Label Learning. IRI 2019: 69-74 - [c5]Keng-Pei Lin, Yihuang Kang, William S. Chao:
A Structure-Behavior Coalescence Design Method for Mobile Social Network Systems. MDM 2019: 497-500 - [i4]Yihuang Kang, I-Ling Cheng, Wenjui Mao, Bowen Kuo, Pei-Ju Lee:
Towards Interpretable Deep Extreme Multi-label Learning. CoRR abs/1907.01723 (2019) - 2018
- [c4]Yihuang Kang, Keng-Pei Lin, I-Ling Cheng:
Topic Diffusion Discovery Based on Sparseness-Constrained Non-Negative Matrix Factorization. IRI 2018: 94-101 - [c3]Shih-Yi Chien, Sharon I-Han Hsiao, Yihuang Kang:
Understanding Students' Intentions in Learning Visual Robotic Programming: An Integration of IS Success Model, Utilitarian Value and Hedonic Value. PACIS 2018: 85 - [i3]Yihuang Kang, Vladimir Zadorozhny:
Process Monitoring Using Maximum Sequence Divergence. CoRR abs/1807.03387 (2018) - [i2]Yihuang Kang, Keng-Pei Lin, I-Ling Cheng:
Topic Diffusion Discovery based on Sparseness-constrained Non-negative Matrix Factorization. CoRR abs/1807.04386 (2018) - [i1]Yihuang Kang, Vladimir Zadorozhny:
Process Discovery using Classification Tree Hidden Semi-Markov Model. CoRR abs/1807.04415 (2018) - 2017
- [c2]Hsin-Ching Huang, San-Yih Hwang, Shanlin Chang, Yihuang Kang:
Forecasting Company Revenue Trend Using Financial News. PACIS 2017: 193 - 2016
- [j1]Yihuang Kang, Vladimir Zadorozhny:
Process monitoring using maximum sequence divergence. Knowl. Inf. Syst. 48(1): 81-109 (2016) - [c1]Yihuang Kang, Vladimir Zadorozhny:
Process Discovery Using Classification Tree Hidden Semi-Markov Model. IRI 2016: 361-368
Coauthor Index
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last updated on 2024-10-30 20:29 CET by the dblp team
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