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Huseyin A. Inan
Huseyin A. Inan
Microsoft Research AI
Verified email at microsoft.com
Title
Cited by
Cited by
Year
Differentially Private Fine-tuning of Language Models
D Yu, S Naik, A Backurs, S Gopi, HA Inan, G Kamath, J Kulkarni, YT Lee, ...
arXiv preprint arXiv:2110.06500, 2021
2382021
rTop-k: A Statistical Estimation Approach to Distributed SGD
LP Barnes, HA Inan, B Isik, A Özgür
IEEE Journal on Selected Areas in Information Theory 1 (3), 897-907, 2020
592020
On the optimality of the Kautz-Singleton construction in probabilistic group testing
HA Inan, P Kairouz, M Wootters, A Özgür
IEEE Transactions on Information Theory 65 (9), 5592-5603, 2019
482019
Synthetic text generation with differential privacy: A simple and practical recipe
X Yue, HA Inan, X Li, G Kumar, J McAnallen, H Shajari, H Sun, D Levitan, ...
arXiv preprint arXiv:2210.14348, 2022
472022
Membership Inference Attacks Against NLP Classification Models
V Shejwalkar, HA Inan, A Houmansadr, R Sim
NeurIPS 2021 Workshop Privacy in Machine Learning, 2021
472021
When Does Differentially Private Learning Not Suffer in High Dimensions?
X Li, D Liu, TB Hashimoto, HA Inan, J Kulkarni, YT Lee, A Guha Thakurta
Advances in Neural Information Processing Systems 35, 28616-28630, 2022
422022
Online power control for the energy harvesting multiple access channel
HA Inan, A Ozgur
2016 14th International Symposium on Modeling and Optimization in Mobile, Ad …, 2016
422016
A convolutive bounded component analysis framework for potentially nonstationary independent and/or dependent sources
HA Inan, AT Erdogan
IEEE Transactions on Signal Processing 63 (1), 18-30, 2014
392014
Training Data Leakage Analysis in Language Models
HA Inan, O Ramadan, L Wutschitz, D Jones, V Rühle, J Withers, R Sim
Privacy Preserving Machine Learning Workshop, 2021
38*2021
Convolutive bounded component analysis algorithms for independent and dependent source separation
HA Inan, AT Erdogan
IEEE transactions on neural networks and learning systems 26 (4), 697-708, 2014
382014
Membership Inference on Word Embedding and Beyond
S Mahloujifar, HA Inan, M Chase, E Ghosh, M Hasegawa
arXiv preprint arXiv:2106.11384, 2021
342021
Privacy Regularization: Joint Privacy-Utility Optimization in Language Models
F Mireshghallah, HA Inan, M Hasegawa, V Rühle, T Berg-Kirkpatrick, ...
arXiv preprint arXiv:2103.07567, 2021
312021
Sparse group testing codes for low-energy massive random access
HA Inan, P Kairouz, A Ozgur
2017 55th Annual Allerton Conference on Communication, Control, and …, 2017
26*2017
An extended family of bounded component analysis algorithms
HA Inan, AT Erdogan
2014 48th Asilomar Conference on Signals, Systems and Computers, 442-445, 2014
242014
A Group Testing Approach to Random Access for Short-Packet Communication
HA Inan, S Ahn, P Kairouz, A Ozgur
2019 IEEE International Symposium on Information Theory (ISIT), 96-100, 2019
212019
Sparse combinatorial group testing
HA Inan, P Kairouz, A Özgür
IEEE Transactions on Information Theory 66 (5), 2729-2742, 2019
202019
Capacity of the energy harvesting Gaussian MAC
HA Inan, D Shaviv, A Özgür
IEEE Transactions on Information Theory 64 (4), 2347-2360, 2018
182018
Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
X Tang, R Shin, HA Inan, A Manoel, F Mireshghallah, Z Lin, S Gopi, ...
arXiv preprint arXiv:2309.11765, 2023
162023
Privacy Leakage in Text Classification: A Data Extraction Approach
A Elmahdy, HA Inan, R Sim
arXiv preprint arXiv:2206.04591, 2022
112022
Differentially private model compression
F Mireshghallah, A Backurs, HA Inan, L Wutschitz, J Kulkarni
Advances in Neural Information Processing Systems 35, 29468-29483, 2022
102022
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