Yao-San Lin

Orcid: 0000-0002-5922-5971

According to our database1, Yao-San Lin authored at least 15 papers between 2006 and 2023.

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Bibliography

2023
Improved learning performance for small datasets in high dimensions by new dual-net model for non-linear interpolation virtual sample generation.
Decis. Support Syst., September, 2023

Mega trend diffusion-siamese network oversampling for imbalanced datasets' SVM classification.
Appl. Soft Comput., August, 2023

Generating virtual samples to improve learning performance in small datasets with non-linear and asymmetric distributions.
Neurocomputing, 2023

2022
An Integrated Framework Based on GAN and RBI for Learning with Insufficient Datasets.
Symmetry, 2022

A Novel Classification Method Based on a Two-Phase Technique for Learning Imbalanced Text Data.
Symmetry, 2022

A Boundary-Information-Based Oversampling Approach to Improve Learning Performance for Imbalanced Datasets.
Entropy, 2022

2019
Generating Synthetic Samples to Improve Small Sample Learning with Mixed Numerical and Categorical Attributes.
Proceedings of the 8th International Congress on Advanced Applied Informatics, 2019

2016
Modeling with Insufficient Data to Increase Prediction Stability.
Proceedings of the 5th IIAI International Congress on Advanced Applied Informatics, 2016

2015
Non-parametric Statistical Assistance in Virtual Sample Selection for Small Data Set Prediction.
Proceedings of the 3rd International Conference on Applied Computing and Information Technology, 2015

2012
A non-linear quality improvement model using SVR for manufacturing TFT-LCDs.
J. Intell. Manuf., 2012

2010
The Generalized-Trend-Diffusion modeling algorithm for small data sets in the early stages of manufacturing systems.
Eur. J. Oper. Res., 2010

2009
Constructing marketing decision support systems using data diffusion technology: A case study of gas station diversification.
Expert Syst. Appl., 2009

2008
Learning management knowledge for manufacturing systems in the early stages using time series data.
Eur. J. Oper. Res., 2008

2007
Using mega-trend-diffusion and artificial samples in small data set learning for early flexible manufacturing system scheduling knowledge.
Comput. Oper. Res., 2007

2006
Using virtual sample generation to build up management knowledge in the early manufacturing stages.
Eur. J. Oper. Res., 2006


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