research
∙
11/25/2022
TAOTF: A Two-stage Approximately Orthogonal Training Framework in Deep Neural Networks
The orthogonality constraints, including the hard and soft ones, have be...
share
research
∙
08/05/2022
Data-free Backdoor Removal based on Channel Lipschitzness
Recent studies have shown that Deep Neural Networks (DNNs) are vulnerabl...
research
∙
05/26/2022
Projectively and weakly simultaneously diagonalizable matrices and their applications
Characterizing simultaneously diagonalizable (SD) matrices has been rece...
research
∙
10/05/2021
Jacobi-type algorithms for homogeneous polynomial optimization on Stiefel manifolds with applications to tensor approximations
In this paper, we mainly study the gradient based Jacobi-type algorithms...
research
∙
09/28/2020
Gradient based block coordinate descent algorithms for joint approximate diagonalization of matrices
In this paper, we propose a gradient based block coordinate descent (BCD...
research
∙
12/22/2019
Polar decomposition based algorithms on the product of Stiefel manifolds with applications in tensor approximation
In this paper, based on the matrix polar decomposition, we propose a gen...
research
∙
12/16/2019
On the convergence of Jacobi-type algorithms for Independent Component Analysis
Jacobi-type algorithms for simultaneous approximate diagonalization of s...
research
∙
11/02/2019
Jacobi-type algorithm for low rank orthogonal approximation of symmetric tensors and its convergence analysis
In this paper, we propose a Jacobi-type algorithm to solve the low rank ...
research
∙
02/20/2019
