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Liang-Sian Lin
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2020 – today
- 2024
- [j14]Liang-Sian Lin:
Improving small sample prediction performance via novel nonlinear interpolation virtual sample generation with self-supervised learning. Inf. Sci. 678: 121044 (2024) - 2023
- [j13]Liang-Sian Lin
, Yao-San Lin
Mega trend diffusion-siamese network oversampling for imbalanced datasets' SVM classification. Appl. Soft Comput. 143: 110406 (2023) - [j12]Liang-Sian Lin
Improved learning performance for small datasets in high dimensions by new dual-net model for non-linear interpolation virtual sample generation. Decis. Support Syst. 172: 113996 (2023) - [j11]Liang-Sian Lin
Generating virtual samples to improve learning performance in small datasets with non-linear and asymmetric distributions. Neurocomputing 548: 126408 (2023) - 2022
- [j10]Der-Chiang Li, Qi-Shi Shi, Yao-San Lin
A Boundary-Information-Based Oversampling Approach to Improve Learning Performance for Imbalanced Datasets. Entropy 24(3): 322 (2022) - [j9]Yao-San Lin
An Integrated Framework Based on GAN and RBI for Learning with Insufficient Datasets. Symmetry 14(2): 339 (2022) - [c8]Liang-Sian Lin
IoT-Based Driver Distraction Prevention System. MLIS 2022: 91-98 - [c7]Liang-Sian Lin
Improving Anomaly Detection in IoT-Based Solar Energy System Using SMOTE-PSO and SVM Model. MLIS 2022: 123-131
2010 – 2019
- 2019
- [j8]Der-Chiang Li, Liang-Sian Lin
Using virtual samples to improve learning performance for small datasets with multimodal distributions. Soft Comput. 23(22): 11883-11900 (2019) - [c6]Tung-I Tsai, Chun-Wu Yeh, Liang-Sian Lin
Improving the Learning Accuracy of the Mega Trend Diffusion Technique for Small Data Sets. IIAI-AAI 2019: 573-578 - 2018
- [j7]Der-Chiang Li
Rebuilding sample distributions for small dataset learning. Decis. Support Syst. 105: 66-76 (2018) - [j6]Liang-Sian Lin
An attribute extending method to improve learning performance for small datasets. Neurocomputing 286: 75-87 (2018) - 2017
- [j5]Der-Chiang Li
The attribute-trend-similarity method to improve learning performance for small datasets. Int. J. Prod. Res. 55(7): 1898-1913 (2017) - 2016
- [c5]Hung-Yu Chen, Der-Chiang Li, Liang-Sian Lin
Extending Sample Information for Small Data Set Prediction. IIAI-AAI 2016: 710-714 - [c4]Liang-Sian Lin
Improving Virtual Sample Generation for Small Sample Learning with Dependent Attributes. IIAI-AAI 2016: 715-718 - [c3]Chun-Wu Yeh, Der-Chiang Li, Liang-Sian Lin
A Learning Approach with Under-and Over-Sampling for Imbalanced Data Sets. IIAI-AAI 2016: 725-729 - 2015
- [c2]Liang-Sian Lin
Generating Multi-modality Virtual Samples with Soft DBSCAN for Small Data Set Learning. ACIT-CSI 2015: 363-368 - [c1]Yao-San Lin
Non-parametric Statistical Assistance in Virtual Sample Selection for Small Data Set Prediction. ACIT-CSI 2015: 369-373 - 2014
- [j4]Der-Chiang Li
Improving learning accuracy by using synthetic samples for small datasets with non-linear attribute dependency. Decis. Support Syst. 59: 286-295 (2014) - [j3]Der-Chiang Li
Generating information for small data sets with a multi-modal distribution. Decis. Support Syst. 66: 71-81 (2014) - 2013
- [j2]Der-Chiang Li
A new approach to assess product lifetime performance for small data sets. Eur. J. Oper. Res. 230(2): 290-298 (2013) - 2011
- [j1]Wen-Chuan Lee, Jong-Wuu Wu, Mei-Ling Hong, Liang-Sian Lin
Assessing the lifetime performance index of Rayleigh products based on the Bayesian estimation under progressive type II right censored samples. J. Comput. Appl. Math. 235(6): 1676-1688 (2011)
Coauthor Index
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