no code implementations • 22 Jan 2021 • M. Nazareth da Costa, R. Attux, A. Cichocki, J. M. T. Romano
We show that the weights of a multidimensional regression model can be learned by means of TT network and the optimization of TT weights is a more robust to the impact of coefficient initialization and hyper-parameter setting.
1 code implementation • 30 Aug 2017 • A. Cichocki, A-H. Phan, Q. Zhao, N. Lee, I. V. Oseledets, M. Sugiyama, D. Mandic
Part 2 of this monograph builds on the introduction to tensor networks and their operations presented in Part 1.
1 code implementation • 4 Sep 2016 • A. Cichocki, N. Lee, I. V. Oseledets, A. -H. Phan, Q. Zhao, D. Mandic
Machine learning and data mining algorithms are becoming increasingly important in analyzing large volume, multi-relational and multi--modal datasets, which are often conveniently represented as multiway arrays or tensors.
Numerical Analysis
2 code implementations • 17 Mar 2014 • A. Cichocki, D. Mandic, A-H. Phan, C. Caiafa, G. Zhou, Q. Zhao, L. De Lathauwer
The widespread use of multi-sensor technology and the emergence of big datasets has highlighted the limitations of standard flat-view matrix models and the necessity to move towards more versatile data analysis tools.
Numerical Analysis