1. komponenta

Lecture type	Total
Lectures	45

* Load is given in academic hour (1 academic hour = 45 minutes)

1. TensorTrain decomposition, I. Oseledets, SIAM J. Sci. Comput. Vol. 33, No. 5, 2011.
2. Tensor-Train decomposition for image recognition, D. Brandoni, V. Simoncini, HAL-02196526, 2019.
3. Diffusion maps, spectral clustering and reaction coordinates of dynamical systems, B. Nadler, S. Lafon, R. R, Coifman, I. G. Kevrekidis, Appl. Comput. Harmonic Analysis 21, 2006.
4. Matrix Methods in Data Mining and Pattern Recognition, Lars Elden, SIAM, 2007.
5. Handwritten digit classification using higher order singular value decomposition, B. Savas, L. Elden, Pattern Recognition 40(3), 2007.
6. Diffusion maps, R. R. Coifman, S. Lafon, Appl. Comput. Harmonic Analysis 21, 2006.

Enrollment :
Attended : Matrix and tensor methods in data analysis

Examination :
Passed : Matrix and tensor methods in data analysis

Izborni modul Modeliranje i pretraživanje baza podataka - Regular study - Applied Mathematics

Izborni modul Modeliranje i pretraživanje baza podataka - Regular study - Applied Mathematics

Izborni modul Modeliranje i pretraživanje baza podataka - Regular study - Applied Mathematics

Izborni modul Modeliranje i pretraživanje baza podataka - Regular study - Applied Mathematics