| 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 | 269 | 2021 |
| 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 | 61 | 2020 |
| 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 | 59 | 2022 |
| Membership Inference Attacks Against NLP Classification Models V Shejwalkar, HA Inan, A Houmansadr, R Sim NeurIPS 2021 Workshop Privacy in Machine Learning, 2021 | 52 | 2021 |
| 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 | 49 | 2019 |
| 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 | 48 | 2022 |
| 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 | 42* | 2021 |
| 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 | 42 | 2016 |
| 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 | 41 | 2014 |
| 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 | 39 | 2014 |
| Membership Inference on Word Embedding and Beyond S Mahloujifar, HA Inan, M Chase, E Ghosh, M Hasegawa arXiv preprint arXiv:2106.11384, 2021 | 37 | 2021 |
| 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 | 34 | 2021 |
| 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 | 28* | 2017 |
| 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 | 26 | 2023 |
| An extended family of bounded component analysis algorithms HA Inan, AT Erdogan 2014 48th Asilomar Conference on Signals, Systems and Computers, 442-445, 2014 | 25 | 2014 |
| 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 | 23 | 2019 |
| Sparse combinatorial group testing HA Inan, P Kairouz, A Özgür IEEE Transactions on Information Theory 66 (5), 2729-2742, 2019 | 21 | 2019 |
| Capacity of the energy harvesting Gaussian MAC HA Inan, D Shaviv, A Özgür IEEE Transactions on Information Theory 64 (4), 2347-2360, 2018 | 18 | 2018 |
| Differentially private model compression F Mireshghallah, A Backurs, HA Inan, L Wutschitz, J Kulkarni Advances in Neural Information Processing Systems 35, 29468-29483, 2022 | 13 | 2022 |
| Privacy Leakage in Text Classification: A Data Extraction Approach A Elmahdy, HA Inan, R Sim arXiv preprint arXiv:2206.04591, 2022 | 13 | 2022 |
Ayfer OzgurAssociate Professor of Electrical Engineering, Stanford UniversityVerified email at stanford.edu
