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2020 – today
- 2022
[c7]Yingwei Li, Tiffany Chen, Maya Kabkab, Ruichi Yu, Longlong Jing, Yurong You, Hang Zhao:
R4D: Utilizing Reference Objects for Long-Range Distance Estimation. ICLR 2022- [i4]Yingwei Li, Tiffany Chen, Maya Kabkab, Ruichi Yu, Longlong Jing, Yurong You
, Hang Zhao:
R4D: Utilizing Reference Objects for Long-Range Distance Estimation. CoRR abs/2206.04831 (2022)
2010 – 2019
- 2018
- [b1]Maya Kabkab:
Learning Along the Edge of Deep Neural Networks. University of Maryland, College Park, MD, USA, 2018 - [c6]Maya Kabkab, Pouya Samangouei, Rama Chellappa:
Task-Aware Compressed Sensing With Generative Adversarial Networks. AAAI 2018: 2297-2304 - [c5]Pouya Samangouei, Maya Kabkab, Rama Chellappa:
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models. ICLR (Poster) 2018 - [i3]Maya Kabkab, Pouya Samangouei, Rama Chellappa:
Task-Aware Compressed Sensing with Generative Adversarial Networks. CoRR abs/1802.01284 (2018) - [i2]Pouya Samangouei, Maya Kabkab, Rama Chellappa:
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models. CoRR abs/1805.06605 (2018) - 2017
- [c4]Maya Kabkab:
The case for spatial pooling in deep convolutional sparse coding. ACSSC 2017: 367-371 - 2016
- [c3]Maya Kabkab, Emily M. Hand, Rama Chellappa:
On the size of Convolutional Neural Networks and generalization performance. ICPR 2016: 3572-3577 - [i1]Maya Kabkab, Azadeh Alavi, Rama Chellappa:
DCNNs on a Diet: Sampling Strategies for Reducing the Training Set Size. CoRR abs/1606.04232 (2016) - 2015
- [j1]Richard J. La, Maya Kabkab:
A New Random Graph Model with Self-Optimizing Nodes: Connectivity and Diameter. Internet Math. 11(6): 528-554 (2015) - 2013
- [c2]Richard J. La, Maya Kabkab:
A new graph model with random edge values: Connectivity and diameter. Allerton 2013: 861-868 - 2012
- [c1]Maya Kabkab, Richard J. La:
Long run equilibria in social games with coordination reward. CISS 2012: 1-6
Coauthor Index
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