Author

OH Asnaz

Paul G. Allen School of Computer Science and Engineering, University of Washington - Cited by 10,127 - Machine Learning - Privacy

Biography

OH Asnaz is affiliated to Institute of Experimental and Applied Physics, Experimental Plasma Physics. He is a recipient of many awards and grants for his valuable contributions and discoveries in major area of subject research. His international experience includes various programs, contributions and participation in different countries for diverse fields of study.  His research interests reflect in his wide range of publications in various national and international journals.  
Title
Cited by
Year
Deepcode: Feedback codes via deep learning
H Kim, Y Jiang, S Kannan, S Oh, P ViswanathIEEE Journal on Selected Areas in Information Theory 1 (1), 194-206, 2020202
129
2020
Optimal transport mapping via input convex neural networks
A Makkuva, A Taghvaei, S Oh, J LeeInternational Conference on Machine Learning, 6672-6681, 2020202
116
2020
Infogan-cr and modelcentrality: Self-supervised model training and selection for disentangling gans
Z Lin, K Thekumparampil, G Fanti, S Ohinternational conference on machine learning, 6127-6139, 2020102202
102
2020
Learn codes: Inventing low-latency codes via recurrent neural networks
Y Jiang, H Kim, H Asnani, S Kannan, S Oh, P ViswanathIEEE Journal on Selected Areas in Information Theory 1 (1), 207-216, 2020202
79
2020
SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics
J Hayase, W Kong, R Somani, S OhInternational Conference on Machine Learning, 2021, 202172202
72
2021
Privacy-utility tradeoffs in routing cryptocurrency over payment channel networks
W Tang, W Wang, G Fanti, S OhProceedings of the ACM on Measurement and Analysis of Computing Systems 4 (2 …, 2020202
57
2020
Gradient inversion with generative image prior
J Jeon, K Lee, S Oh, J OkAdvances in neural information processing systems 34, 29898-29908, 2021202
55
2021
Meta-learning for mixed linear regression
W Kong, R Somani, Z Song, S Kakade, S OhInternational Conference on Machine Learning, 5394-5404, 2020202
46
2020
Robust and differentially private mean estimation
X Liu, W Kong, S Kakade, S OhAdvances in neural information processing systems 34, 3887-3901, 2021202
46
2021
Physical layer communication via deep learning
H Kim, S Oh, P ViswanathIEEE Journal on Selected Areas in Information Theory 1 (1), 5-18, 2020202
37
2020
Differential privacy and robust statistics in high dimensions
X Liu, W Kong, S OhConference on Learning Theory, 1167-1246, 2022202
23
2022
Ko codes: inventing nonlinear encoding and decoding for reliable wireless communication via deep-learning
AV Makkuva, X Liu, MV Jamali, H Mahdavifar, S Oh, P ViswanathInternational Conference on Machine Learning, 7368-7378, 2021202
22
2021
Projection efficient subgradient method and optimal nonsmooth frank-wolfe method
KK Thekumparampil, P Jain, P Netrapalli, S OhAdvances in Neural Information Processing Systems 33, 12211-12224,
20
2020
Proof-of-stake longest chain protocols: Security vs predictability
V Bagaria, A Dembo, S Kannan, S Oh, D Tse, P Viswanath, X Wang, ...Proceedings of the 22 ACM Workshop on Developments in Consensus, 29-42, 222
20
2022
Lifted Primal-Dual Method for Bilinearly Coupled Smooth Minimax Optimization
K Koshy Thekumparampil, N He, S OhAISTATS 2022, 202219202
19
2022
Efficient algorithms for federated saddle point optimization
C Hou, KK Thekumparampil, G Fanti, S OharXiv preprint arXiv:2102.06333, 2021202
17
2021
Statistically and computationally efficient linear meta-representation learning
KK Thekumparampil, P Jain, P Netrapalli, S OhAdvances in Neural Information Processing Systems 34, 18487-18500, 202116202
16
2021
Quality not quantity: On the interaction between dataset design and robustness of clip
T Nguyen, G Ilharco, M Wortsman, S Oh, L SchmidtAdvances in Neural Information Processing Systems 35, 2022, 2022202
15
2022
FeDChain: Chained algorithms for near-optimal communication cost in federated learning
C Hou, KK Thekumparampil, G Fanti, S OhInternational Conference on Learning Representations (ICLR), 202214202
14
2022
Reed-Muller subcodes: Machine learning-aided design of efficient soft recursive decoding
MV Jamali, X Liu, AV Makkuva, H Mahdavifar, S Oh, P Viswanath2021 IEEE International Symposium on Information Theory (ISIT), 1088-1093, 2021202
13
2021

Referred From: https://scholar.google.com/citations?user=N6AWeX0AAAAJ&hl=en

Cited by
Citations 10127
h-index 42
i10-index 87
Open Access Journals