Thanh-Binh Le

A hybrid selection method of helpful unlabeled data applicable for semi-supervised learning algorithms

Sang-Woon Kim, Thanh-Binh Le, 2014, The 18th IEEE International Symposium on Consumer Electronics (ISCE 2014).

Transfor m ation Based Methods Extracting Multiple Views for Co-training Algorith m s

Thanh-Binh Le, Sang-Woon Ki, 2017 .

Modified criterion to select useful unlabeled data for improving semi-supervised support vector machines

Sang-Woon Kim, Thanh-Binh Le, Sang-Woon Kim, 2015, Pattern Recognit. Lett..

Comparison of Adjusted Methods for Selecting Useful Unlabeled Data for Semi-Supervised Learning Algorithms

Sang-Woon Kim, Thanh-Binh Le, Sang-Woon Kim, 2015, IEA/AIE.

Simply recycled selection and incrementally reinforced selection methods applicable for semi-supervised learning algorithms

Sang-Woon Kim, Thanh-Binh Le, Sang-Woon Kim, 2014, 2014 International Conference on Electronics, Information and Communications (ICEIC).

A Hybrid Selection Method of Helpful Unlabeled Data Applicable for Semi-Supervised Learning Algorithm

Sang-Woon Kim, Thanh-Binh Le, Sang-Woon Kim, 2014 .

On incrementally using a small portion of strong unlabeled data for semi-supervised learning algorithms

Sang-Woon Kim, Thanh-Binh Le, Sang-Woon Kim, 2014, Pattern Recognit. Lett..

Multi-view based unlabeled data selection using feature transformation methods for semiboost learning

Sang-Woon Kim, Sugwon Hong, Thanh-Binh Le, 2017, Neurocomputing.

On measuring confidence levels using multiple views of feature set for useful unlabeled data selection

Sang-Woon Kim, Thanh-Binh Le, Sang-Woon Kim, 2016, Neurocomputing.