Thanh-Binh Le

发表

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

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

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).

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.

Useful Unlabeled Data Selection Using Cuckoo Search Algorithm for SemiBoost Learning

Sang-Woon Kim, Trung Hai Nguyen, Thanh-Binh Le, 2016 .

Feature Decomposition Using Mutual Information for SemiBoost Learning

Sang-Woon Kim, Thanh-Binh Le, 2015 .

On Selecting Helpful Unlabeled Data for Improving Semi-Supervised Support Vector Machines

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

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..

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

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

Feature learning for representing sparse networks based on random walks

Giang Son Tran, Hoai Bac Le, Thanh-Binh Le, 2020, Intell. Data Anal..

Choosing unlabeled examples for SemiBoost using modified cuckoo search algorithms

Sang-Woon Kim, Trung Hai Nguyen, Thanh-Binh Le, 2016, 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD).

D-20-6 Classification Using Single-view or Multi-views: Which One is Better?

Sang-Woon Kim, Thanh-Binh Le, 2015 .

On Improving Semi-supervised Marginboost Incrementally using Strong Unlabeled Data

Sang-Woon Kim, Thanh-Binh Le, 2012, ICPRAM.

Story Disambiguation: Tracking Evolving News Stories across News and Social Streams pdf

Neil J. Hurley, Bichen Shi, Georgiana Ifrim, 2018, ArXiv.

On Selecting Useful Unlabeled Data Using Multi-view Learning Techniques

Sang-Woon Kim, Thanh-Binh Le, 2015, ICPRAM.

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.

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..