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Pedro Sandoval-Segura
Pedro Sandoval-Segura
Verified email at cs.umd.edu - Homepage
Title
Cited by
Cited by
Year
An information-theoretic perspective on overfitting and underfitting
D Bashir, GD Montañez, S Sehra, PS Segura, J Lauw
AI 2020: Advances in Artificial Intelligence: 33rd Australasian Joint …, 2020
572020
Autoregressive perturbations for data poisoning
P Sandoval-Segura, V Singla, J Geiping, M Goldblum, T Goldstein, ...
Advances in Neural Information Processing Systems 35, 27374-27386, 2022
242022
Program language translation using a grammar-driven tree-to-tree model
M Drissi, O Watkins, A Khant, V Ojha, P Sandoval, R Segev, E Weiner, ...
ICML Workshop on Neural Abstract Machines and Program Induction, 2018
242018
Poisons that are learned faster are more effective
P Sandoval-Segura, V Singla, L Fowl, J Geiping, M Goldblum, D Jacobs, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
102022
Harvey mudd college at semeval-2019 task 4: The clint buchanan hyperpartisan news detector
M Drissi, P Sandoval, V Ojha, J Medero
Proceedings of the 13th International Workshop on Semantic Evaluation, 2019
82019
The labeling distribution matrix (LDM): a tool for estimating machine learning algorithm capacity
PS Segura, J Lauw, D Bashir, K Shah, S Sehra, D Macias, G Montanez
12th International Conference on Agents and Artificial Intelligence, 2019
72019
What Can We Learn from Unlearnable Datasets?
P Sandoval-Segura, V Singla, J Geiping, M Goldblum, T Goldstein
Advances in Neural Information Processing Systems 36, 2024
32024
JPEG compressed images can bypass protections against ai editing
P Sandoval-Segura, J Geiping, T Goldstein
arXiv preprint arXiv:2304.02234, 2023
22023
AutoProtoNet: Interpretability for Prototypical Networks
P Sandoval-Segura, W Lawson
arXiv preprint arXiv:2204.00929, 2022
22022
A Simple and Efficient Baseline for Data Attribution on Images
V Singla, P Sandoval-Segura, M Goldblum, J Geiping, T Goldstein
arXiv preprint arXiv:2311.03386, 2023
2023
Adversarially robust segmentation models learn perceptually-aligned gradients
P Sandoval-Segura
arXiv preprint arXiv:2204.01099, 2022
2022
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