PhD. VO XUAN THANH | Faculty of Mathematics & Statistics


	PhD. VO XUAN THANH
	PhD. 2015
	Lecturer
	voxuanthanh@tdtu.edu.vn

A. Education and professional activities

1. Education and degrees

2012-2015: PhD in Computer Science at University of Lorraine, France
2011-2012: Msc in Mathematics at University of Tours, France
2007-2011: BS in Mathematics and Informatics at University of Science, Vietnam; Honor program

2. Professional activities

2020 - present: Lecturer at Ton Duc Thang University, Vietnam
2015 - 2017: Postdoc at University of Lorraine, France

3. Research interests

+ DC optimization

+ Machine Learning

4. Conferences

[12] H. M. Le and V. Xuan thanh, “Reweighted L1 Algorithm for Robust Principal Component Analysis”. In “Proceedings of the 6th International Conference on Computer Science, Applied Mathematics and Applications, ICCSAMA 2019”, AISC 1121, pp. 133-142, Springer 2020

[11] V. Xuan thanh . T. Bach, H. A. Le Thi, T. Pham Dinh, “Ramp Loss Support Vector Data Description”. In “Proceedings of the 9th Asian Conference on Intelligent Information and Database Systems”, part I, LNAI 10191, pp. 421-431, Springer 2017

[10] X. T. Vo, H. A. Le Thi and T. Pham Dinh, “Robust Optimization for Clustering”. In “Proceedings of the 8th Asian Conference on Intelligent Information and Database Systems”, part II, LNAI 9622, pp. 671-680, Springer 2016

[9] X. T. Vo, H. A. Le Thi, T. Pham Dinh. and T. B. T. Nguyen, “DC Programming and DCA for Dictionary Learning”. In “Proceedings of 7th International Conference on Computational Collective Intelligence Technologies and Applications”, part I, LNAI 9329, pp. 295-304, Springer 2015

[8] T. B. T. Nguyen, H. A. Le Thi, H. M. Le and X. T. Vo, “DC approximation approach for L0-minimization in compressed sensing”. In “Proceedings of 3rd International Conference on Computer Science, Applied Mathematics and Applications”, AISC 358, pp. 37-48, Springer 2015

[7] X. T. Vo and H. A. Le Thi, “Robust Optimization for Clustering”. The 27th European Conference on Operational Research (EURO-INFORMS), Glasgow, UK, July 12 - 15, 2015

[6] H. A. Le Thi, X. T. Vo and T. Pham Dinh, “DC programming and DCA for nonnegative matrix factorization”. In “Proceedings of 6th International Conference on Computational Collective Intelligence Technologies and Applications”, LNAI 8733, pp. 573-582, Springer 2014

[5] H. A. Le Thi, A. V. Le, X. T. Vo and Z. Ahmed, “A Filter Based Feature Selection Approach in MSVM Using DCA and Its Application in Network Intrusion Detection”. In “ACIIDS 2014: Proceedings of the 6th Asian Conference on Intelligence Information and Database Systems”, LNAI 8398, pp. 403–413, Springer 2014

[4] X. T. Vo, H. A. Le Thi and T. Pham Dinh, “DC programming and DCA for Dictionary Learning”. The 20th Conference of the International Federation of Operational Research Societies (IFORS) Barcelona, Spain, July 13 - 18, 2014

[3] X. T. Vo, H. A. Le Thi and T. Pham Dinh, “DC Programming and DCA for Nonnegative Matrix Factorization”. Conférence sur l’Optimisation, la Planification et la Fusion Multi-Capteurs (PFMC 2013), Brest, France, October 23-24, 2013

[2] X. T. Vo, H. A. Le Thi and T. Pham Dinh, “DC Programming and DCA for Nonnegative Matrix Factorization”. The 26th European Conference on Operational Research (EURO-INFORMS), Rome, Italy, July 1 - 4, 2013

[1] H. A. Le Thi, X. T. Vo and T. Pham Dinh, “Robust Feature Selection for SVMs under Uncertain Data”. In “Proceedings of the 13th Industrial Conference on Advances in Data Mining”, LNAI 7987, pp. 151–165, Springer 2013

B. Publications

[3] H. A. Le Thi, X. T. Vo and T. Pham Dinh (2016) Efficient Nonnegative Matrix Factorization by DC programming and DCA. Neural Computation 28(6): 1163-1216 (SCIE)

[2] H. A. Le Thi, T. Pham Dinh, H. M. Le and X. T. Vo (2015) DC approximation approaches for sparse optimization. European Journal of Operational Research 244(1): 26-46 (SCIE)

[1] H. A. Le Thi, X. T. Vo and T. Pham Dinh (2014) Feature Selection for SVMs under Uncertain Data: Robust optimization based on Difference of Convex functions Algorithms. Neural Networks 59: 36-50 (SCIE)