• / Prof. Manolis Tsakiris / Manolis Tsakiris 助理教授、研究员
    电话:(021) 20685356
    Email: mtsakiris@@shanghaitech.edu.cn
    办公室: 上海市浦东新区华夏中路393号信息学院1C-303A室
    专业方向: 计算机科学与技术
Prof. Manolis Tsakiris / Manolis Tsakiris 助理教授、研究员

电 话:(021) 20685356
Email :mtsakiris@@shanghaitech.edu.cn
个人主页: https://sites.google.com/site/manolisctsakiris/
专业方向: 计算机科学与技术


  • Data Science

  • Machine Learning

  • Commutative Algebra


Manolis Tsakiris is an electrical engineering and computer science graduate of the National Technical University of Athens, Greece. He holds an M.S. degree in signal processing from Imperial College London, UK, and a PhD degree from Johns Hopkins University, USA, in theoretical machine learning, under the supervision of Prof. Rene Vidal. Since August 2017 he is an assistant professor at the School of Information Science and Technology (SIST) at ShanghaiTech University. His main research interests are subspace learning from data and related problems in commutative algebra. 


1. Z. Zhu, Y. Wang, D. P. Robinson, D. Naiman, R. Vidal, M. C. Tsakiris, Dual principal component pursuit: Improved analysis and efficient algorithms, Neural Information Processing Systems (NIPS), 2018.

2. M. C. Tsakiris and R. Vidal. Dual principal component pursuit, Journal of Machine Learning Research, 2018.

3. M. C. Tsakiris and R. Vidal. Theoretical analysis of sparse subspace clustering with missing entries, International Conference on Machine Leanring, 2018.

4. M. Tsakiris and R. Vidal. Hyperplane clustering via dual principal component pursuit. International Conference on Machine Learning, 2017.

5. M. Tsakiris and R. Vidal. Algebraic clustering of affine subspaces. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017.

6. M. Tsakiris and R. Vidal. Filtrated algebraic subspace clustering. SIAM Journal of Imaging Sciences, 2017.

7. M. Tsakiris and D. Tarraf. Algebraic decompositions of dynamic programming problems with linear dynamics. Systems and Control Letters, 2015.

8. M. Tsakiris, C. Lopes and V. Nascimento. An array recursive least- squares algorithm with generic nonfading regularization matrix. IEEE Signal Processing Letters, 2010.