Artículos con órdenes de acceso público - Bhavya KailkhuraMás información
No disponibles en ningún lugar: 5
Decentralized joint sparsity pattern recovery using 1-bit compressive sensing
S Kafle, B Kailkhura, T Wimalajeewa, PK Varshney
2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2016
Órdenes: US National Science Foundation
Secure distributed detection of sparse signals via Falsif I cation of local compressive measurements
C Li, G Li, B Kailkhura, PK Varshney
IEEE Transactions on Signal Processing 67 (18), 4696-4706, 2019
Órdenes: US National Science Foundation, US Department of Energy, National Natural …
Fault-tolerant deep neural networks for processing-in-memory based autonomous edge systems
S Wang, G Yuan, X Ma, Y Li, X Lin, B Kailkhura
2022 Design, Automation & Test in Europe Conference & Exhibition (DATE), 424-429, 2022
Órdenes: US National Science Foundation, US Department of Energy
Collaborative spectrum sensing in the presence of Byzantine attacks
B Kailkhura, A Vempaty, PK Varshney
Cooperative and graph signal processing, 505-522, 2018
Órdenes: US Department of Energy
More or less (mol): Defending against multiple perturbation attacks on deep neural networks through model ensemble and compression
H Cheng, K Xu, Z Li, P Zhao, C Wang, X Lin, B Kailkhura, R Goldhahn
2022 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops …, 2022
Órdenes: US Department of Energy
Disponibles en algún lugar: 69
Automatic perturbation analysis for scalable certified robustness and beyond
K Xu, Z Shi, H Zhang, Y Wang, KW Chang, M Huang, B Kailkhura, X Lin, ...
Advances in Neural Information Processing Systems 33, 1129-1141, 2020
Órdenes: US National Science Foundation, US Department of Energy, National Natural …
Anomalous example detection in deep learning: A survey
S Bulusu, B Kailkhura, B Li, PK Varshney, D Song
IEEE Access 8, 132330-132347, 2020
Órdenes: US Department of Energy
Mix-n-match: Ensemble and compositional methods for uncertainty calibration in deep learning
J Zhang, B Kailkhura, TYJ Han
International conference on machine learning, 11117-11128, 2020
Órdenes: US Department of Energy
A primer on zeroth-order optimization in signal processing and machine learning: Principals, recent advances, and applications
S Liu, PY Chen, B Kailkhura, G Zhang, AO Hero III, PK Varshney
IEEE Signal Processing Magazine 37 (5), 43-54, 2020
Órdenes: US Department of Energy
Zeroth-order stochastic variance reduction for nonconvex optimization
S Liu, B Kailkhura, PY Chen, P Ting, S Chang, L Amini
Advances in Neural Information Processing Systems 31 (2018): 3727-3737, 2018
Órdenes: US Department of Energy
Reliable and explainable machine-learning methods for accelerated material discovery
B Kailkhura, B Gallagher, S Kim, A Hiszpanski, TYJ Han
npj Computational Materials 5 (1), 108, 2019
Órdenes: US Department of Energy
Explainable machine learning in materials science
X Zhong, B Gallagher, S Liu, B Kailkhura, A Hiszpanski, TYJ Han
npj computational materials 8 (1), 204, 2022
Órdenes: US Department of Energy
Generative counterfactual introspection for explainable deep learning
S Liu, B Kailkhura, D Loveland, Y Han
2019 IEEE global conference on signal and information processing (GlobalSIP …, 2019
Órdenes: US Department of Energy
Mimicgan: Robust projection onto image manifolds with corruption mimicking
R Anirudh, JJ Thiagarajan, B Kailkhura, PT Bremer
International Journal of Computer Vision 128, 2459-2477, 2020
Órdenes: US Department of Energy
On the design of black-box adversarial examples by leveraging gradient-free optimization and operator splitting method
P Zhao, S Liu, PY Chen, N Hoang, K Xu, B Kailkhura, X Lin
Proceedings of the IEEE/CVF International Conference on Computer Vision, 121-130, 2019
Órdenes: US National Science Foundation
Nanomaterial synthesis insights from machine learning of scientific articles by extracting, structuring, and visualizing knowledge
AM Hiszpanski, B Gallagher, K Chellappan, P Li, S Liu, H Kim, J Han, ...
Journal of chemical information and modeling 60 (6), 2876-2887, 2020
Órdenes: US Department of Energy
Performance modeling under resource constraints using deep transfer learning
A Marathe, R Anirudh, N Jain, A Bhatele, J Thiagarajan, B Kailkhura, ...
Proceedings of the International Conference for High Performance Computing …, 2017
Órdenes: US Department of Energy
A Winning Hand: Compressing Deep Networks Can Improve Out-Of-Distribution Robustness
J Diffenderfer, BR Bartoldson, S Chaganti, J Zhang, B Kailkhura
NeurIPS 2021, 2021
Órdenes: US Department of Energy
G-pate: Scalable differentially private data generator via private aggregation of teacher discriminators
Y Long, B Wang, Z Yang, B Kailkhura, A Zhang, C Gunter, B Li
Advances in Neural Information Processing Systems 34, 2965-2977, 2021
Órdenes: US National Science Foundation, US Department of Energy
Fedcluster: Boosting the convergence of federated learning via cluster-cycling
C Chen, Z Chen, Y Zhou, B Kailkhura
2020 IEEE International Conference on Big Data (Big Data), 5017-5026, 2020
Órdenes: US Department of Energy
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