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ORCIDEmilio Rafael Balda
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2020 – today
- 2020
[c7]Emilio Rafael Balda, Niklas Koep, Arash Behboodi, Rudolf Mathar:
Adversarial Risk Bounds through Sparsity based Compression. AISTATS 2020: 3816-3825
2010 – 2019
- 2019
- [b1]Emilio Rafael Balda Cañizares:
Robustness analysis of deep neural networks in the presence of adversarial perturbations and noisy labels. RWTH Aachen University, Germany, Apprimus Verlag 2019, ISBN 978-3-86359-802-0, pp. 1-125 - [j1]Emilio Rafael Balda
, Arash Behboodi, Rudolf Mathar:
Perturbation Analysis of Learning Algorithms: Generation of Adversarial Examples From Classification to Regression. IEEE Trans. Signal Process. 67(23): 6078-6091 (2019) - [c6]Peter Langenberg, Emilio Rafael Balda, Arash Behboodi, Rudolf Mathar:
On the Robustness of Support Vector Machines against Adversarial Examples. ICSPCS 2019: 1-6 - [i5]Peter Langenberg, Emilio Rafael Balda, Arash Behboodi, Rudolf Mathar:
On the Effect of Low-Rank Weights on Adversarial Robustness of Neural Networks. CoRR abs/1901.10371 (2019) - [i4]Emilio Rafael Balda, Arash Behboodi, Niklas Koep, Rudolf Mathar:
Adversarial Risk Bounds for Neural Networks through Sparsity based Compression. CoRR abs/1906.00698 (2019) - 2018
- [c5]Emilio Rafael Balda, Arash Behboodi, Rudolf Mathar:
On Generation of Adversarial Examples using Convex Programming. ACSSC 2018: 60-65 - [c4]Emilio Rafael Balda, Arash Behboodi, Rudolf Mathar:
An Information Theoretic View on Learning of Artificial Neural Networks. ICSPCS 2018: 1-8 - [i3]Emilio Rafael Balda, Arash Behboodi, Rudolf Mathar:
On Generation of Adversarial Examples using Convex Programming. CoRR abs/1803.03607 (2018) - [i2]Emilio Rafael Balda, Arash Behboodi, Rudolf Mathar:
Perturbation Analysis of Learning Algorithms: A Unifying Perspective on Generation of Adversarial Examples. CoRR abs/1812.07385 (2018) - 2017
- [c3]Sher Ali Cheema, Emilio Rafael Balda, Amir Weiss, Arie Yeredor, Martin Haardt:
Analytical performance analysis of the Semi-Algebraic framework for approximate CP decompositions via SImultaneous matrix diagonalizations (SECSI). ACSSC 2017: 703-707 - [c2]Emilio Rafael Balda, Sher Ali Cheema, Amir Weiss, Arie Yeredor, Martin Haardt:
Perturbation analysis of Joint Eigenvalue Decomposition Algorithms. ICASSP 2017: 3101-3105 - [i1]Sher Ali Cheema, Emilio Rafael Balda, Yao Cheng, Martin Haardt, Amir Weiss, Arie Yeredor:
First-Order Perturbation Analysis of the SECSI Framework for the Approximate CP Decomposition of 3-D Noise-Corrupted Low-Rank Tensors. CoRR abs/1710.06693 (2017) - 2016
- [c1]Emilio Rafael Balda, Sher Ali Cheema, Jens Steinwandt, Martin Haardt, Amir Weiss, Arie Yeredor:
First-order perturbation analysis of low-rank tensor approximations based on the truncated HOSVD. ACSSC 2016: 1723-1727
Coauthor Index
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