| Perturbation analysis of learning algorithms: Generation of adversarial examples from classification to regression ER Balda, A Behboodi, R Mathar IEEE Transactions on Signal Processing 67 (23), 6078-6091, 2019 | 28 | 2019 |
| Adversarial examples in deep neural networks: An overview ER Balda, A Behboodi, R Mathar Deep learning: algorithms and applications, 31-65, 2020 | 21 | 2020 |
| On generation of adversarial examples using convex programming ER Balda, A Behboodi, R Mathar 2018 52nd Asilomar Conference on Signals, Systems, and Computers, 60-65, 2018 | 17 | 2018 |
| On the effect of low-rank weights on adversarial robustness of neural networks P Langenberg, ER Balda, A Behboodi, R Mathar arXiv preprint arXiv:1901.10371, 2019 | 14 | 2019 |
| First-order perturbation analysis of low-rank tensor approximations based on the truncated HOSVD ER Balda, SA Cheema, J Steinwandt, M Haardt, A Weiss, A Yeredor 2016 50th Asilomar Conference on Signals, Systems and Computers, 1723-1727, 2016 | 13 | 2016 |
| Perturbation analysis of joint eigenvalue decomposition algorithms ER Balda, SA Cheema, A Weiss, A Yeredor, M Haardt 2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017 | 10 | 2017 |
| Adversarial Risk Bounds through Sparsity based Compression E Balda, N Koep, A Behboodi, R Mathar International Conference on Artificial Intelligence and Statistics, 3816-3825, 2020 | 9* | 2020 |
| On the robustness of support vector machines against adversarial examples P Langenberg, E Balda, A Behboodi, R Mathar 2019 13th International Conference on Signal Processing and Communication …, 2019 | 9 | 2019 |
| An information theoretic view on learning of artificial neural networks ER Balda, A Behboodi, R Mathar 2018 12th International Conference on Signal Processing and Communication …, 2018 | 8 | 2018 |
| Fundamentals of Data Analytics R Mathar, G Alirezaei, E Balda, A Behboodi Springer, Cham, Switzerland, 2020 | 7 | 2020 |
| Unique word DMT schemes for optical systems with intensity modulation and direct detection SA Cheema, ER Balda, M Wolf, M Haardt Journal of Lightwave Technology 35 (18), 3862-3869, 2017 | 5 | 2017 |
| First-order perturbation analysis of the SECSI framework for the approximate CP decomposition of 3-D noise-corrupted low-rank tensors SA Cheema, ER Balda, Y Cheng, M Haardt, A Weiss, A Yeredor arXiv preprint arXiv:1710.06693, 2017 | 4 | 2017 |
| Support Vector Machines R Mathar, G Alirezaei, E Balda, A Behboodi, R Mathar, G Alirezaei, ... Fundamentals of Data Analytics: With a View to Machine Learning, 83-105, 2020 | 3 | 2020 |
| Analytical Performance Analysis of the SEmi-algebraic framework for approximate CP decompositions via SImultaneous matrix diagonalizations (SECSI) SA Cheema, ER Balda, A Weiss, A Yeredor, M Haardt 2017 51st Asilomar Conference on Signals, Systems, and Computers, 703-707, 2017 | 1 | 2017 |
| Multivariate Distributions and Moments R Mathar, G Alirezaei, E Balda, A Behboodi, R Mathar, G Alirezaei, ... Fundamentals of Data Analytics: With a View to Machine Learning, 35-43, 2020 | | 2020 |
| Prerequisites from Matrix Analysis R Mathar, G Alirezaei, E Balda, A Behboodi, R Mathar, G Alirezaei, ... Fundamentals of Data Analytics: With a View to Machine Learning, 9-33, 2020 | | 2020 |
| Classification and Clustering R Mathar, G Alirezaei, E Balda, A Behboodi, R Mathar, G Alirezaei, ... Fundamentals of Data Analytics: With a View to Machine Learning, 69-81, 2020 | | 2020 |
| Dimensionality Reduction R Mathar, G Alirezaei, E Balda, A Behboodi, R Mathar, G Alirezaei, ... Fundamentals of Data Analytics: With a View to Machine Learning, 45-67, 2020 | | 2020 |
| Ghassan R. Alnwaimi Lucas M Alves Sultangali Arzykulov Muhammad Shoaib Azam C Azurdia, ER Balda, MB Balogun, M Bansal, A Bates, NS Bayev, ... | | |
