Search Results for author:
Found 8 papers, 4 papers with code
A Theoretical Study of The Effects of Adversarial Attacks on Sparse Regression
This paper analyzes $\ell_1$ regularized linear regression under the challenging scenario of having only adversarially corrupted data for training.
A Novel Plug-and-Play Approach for Adversarially Robust Generalization
In this work, we propose a robust framework that employs adversarially robust training to safeguard the machine learning models against perturbed testing data.
Hyperedge Prediction using Tensor Eigenvalue Decomposition
This is further used to propose a hyperedge prediction algorithm.
Identification of Errors-in-Variables ARX Models Using Modified Dynamic Iterative PCA
We propose a novel identification algorithm based on a modified Dynamic Iterative Principal Components Analysis (DIPCA) approach for identifying the EIV-ARX model for single-input, single-output (SISO) systems where the output measurements are corrupted with coloured noise consistent with the ARX model.
Hypergraph Partitioning using Tensor Eigenvalue Decomposition
We also show improvement for the min-cut solution on 2-uniform hypergraphs (graphs) over the standard spectral partitioning algorithm.
Identification of MISO systems in Minimal Realization Form
In this work, we deal with the challenging problem of identifying order, delay in each input of minimal realization form separately while estimating the transfer functions.
Systems and Control Systems and Control
ARX Model Identification using Generalized Spectral Decomposition
This article is concerned with the identification of autoregressive with exogenous inputs (ARX) models.
Systems and Control Systems and Control
Incorporating prior knowledge about structural constraints in model identification
Our proposed method is a wise modification of PCA to utilize structural information.
