| Benchmarking Differential Privacy and Federated Learning for BERT Models P Basu, TS Roy, R Naidu, Z Muftuoglu, S Singh, F Mireshghallah arXiv preprint arXiv:2106.13973, 2021 | 76* | 2021 |
| SS-CAM: Smoothed Score-CAM for sharper visual feature localization H Wang, R Naidu, J Michael arXiv preprint arXiv:2006.14255, 2020 | 75 | 2020 |
| IS-CAM: Integrated Score-CAM for axiomatic-based explanations R Naidu, A Ghosh, Y Maurya, SS Kundu arXiv preprint arXiv:2010.03023, 2020 | 36 | 2020 |
| Dp-sgd vs pate: Which has less disparate impact on model accuracy? A Uniyal, R Naidu, S Kotti, S Singh, PJ Kenfack, F Mireshghallah, A Trask arXiv preprint arXiv:2106.12576, 2021 | 34 | 2021 |
| Pruning has a disparate impact on model accuracy C Tran, F Fioretto, JE Kim, R Naidu Advances in neural information processing systems 35, 17652-17664, 2022 | 21 | 2022 |
| Are chatbots ready for privacy-sensitive applications? an investigation into input regurgitation and prompt-induced sanitization A Priyanshu, S Vijay, A Kumar, R Naidu, F Mireshghallah arXiv preprint arXiv:2305.15008, 2023 | 12 | 2023 |
| Towards quantifying the carbon emissions of differentially private machine learning R Naidu, H Diddee, A Mulay, A Vardhan, K Ramesh, A Zamzam arXiv preprint arXiv:2107.06946, 2021 | 12 | 2021 |
| Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Tools E Black, R Naidu, R Ghani, K Rodolfa, D Ho, H Heidari Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms …, 2023 | 9 | 2023 |
| Fedperf: A practitioners’ guide to performance of federated learning algorithms A Mulay, B Gaspard, R Naidu, S Gonzalez-Toral, S Vineeth, T Semwal, ... NeurIPS 2020 Workshop on Pre-registration in Machine Learning, 302-324, 2021 | 9 | 2021 |
| SR Nayak K, and SS Kundu R Naidu, A Ghosh, Y Maurya IS-CAM: integrated score-cam for axiomatic-based explanations. CoRR, abs …, 2020 | 6 | 2020 |
| Efficient hyperparameter optimization for differentially private deep learning A Priyanshu, R Naidu, F Mireshghallah, M Malekzadeh arXiv preprint arXiv:2108.03888, 2021 | 5 | 2021 |
| K, SRN, and Kundu, SS (2020) R Naidu, A Ghosh, Y Maurya IS-CAM: integrated score-cam for axiomatic-based explanations. CoRR, abs, 2010 | 5 | 2010 |
| When differential privacy meets interpretability: A case study R Naidu, A Priyanshu, A Kumar, S Kotti, H Wang, F Mireshghallah arXiv preprint arXiv:2106.13203, 2021 | 4 | 2021 |
| FedPandemic: a cross-device federated learning approach towards elementary prognosis of diseases during a pandemic A Priyanshu, R Naidu arXiv preprint arXiv:2104.01864, 2021 | 3 | 2021 |
| TeleVital: Enhancing the quality of contactless health assessment J Sunny, J Jogy, R Rout, R Naidu arXiv preprint arXiv:2007.00762, 2020 | 2 | 2020 |
| Personalized differential privacy for ridge regression K Acharya, F Boenisch, R Naidu, J Ziani arXiv preprint arXiv:2401.17127, 2024 | 1 | 2024 |
| Can Causal (and Counterfactual) Reasoning improve Privacy Threat Modelling? R Naidu, N Kagalwalla arXiv preprint arXiv:2207.09746, 2022 | 1 | 2022 |
| Fair Context-Aware Privacy Threat Modelling S Das, R Naidu arXiv preprint arXiv:2207.09750, 2022 | | 2022 |
| When Differential Privacy Meets Interpretability: A Case Study A Priyanshu, R Naidu, A Kumar, S Kotti, H Wang, F Mireshghallah | | |
Niloofar MireshghallahPostdoctoral scholar, University of Washington在 cs.washington.edu 的电子邮件经过验证
