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ORCIDRakshit Naidu
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2020 – today
- 2024
[i17]Krishna Acharya, Franziska Boenisch, Rakshit Naidu, Juba Ziani:
Personalized Differential Privacy for Ridge Regression. CoRR abs/2401.17127 (2024)- 2023
- [c3]Emily Black
, Rakshit Naidu, Rayid Ghani, Kit T. Rodolfa, Daniel E. Ho, Hoda Heidari:
Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Tools. EAAMO 2023: 36:1-36:11 - [i16]Aman Priyanshu, Supriti Vijay, Ayush Kumar, Rakshit Naidu, Fatemehsadat Mireshghallah:
Are Chatbots Ready for Privacy-Sensitive Applications? An Investigation into Input Regurgitation and Prompt-Induced Sanitization. CoRR abs/2305.15008 (2023) - [i15]Emily Black, Rakshit Naidu, Rayid Ghani, Kit T. Rodolfa, Daniel E. Ho, Hoda Heidari:
Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Tools. CoRR abs/2309.17337 (2023) - 2022
- [c2]Cuong Tran, Ferdinando Fioretto, Jung-Eun Kim, Rakshit Naidu:
Pruning has a disparate impact on model accuracy. NeurIPS 2022 - [i14]Tiasa Singha Roy, Priyam Basu, Aman Priyanshu, Rakshit Naidu:
Interpretability of Fine-grained Classification of Sadness and Depression. CoRR abs/2203.10432 (2022) - [i13]Cuong Tran, Ferdinando Fioretto, Jung-Eun Kim, Rakshit Naidu:
Pruning has a disparate impact on model accuracy. CoRR abs/2205.13574 (2022) - [i12]Rakshit Naidu, Navid Kagalwalla:
Can Causal (and Counterfactual) Reasoning improve Privacy Threat Modelling? CoRR abs/2207.09746 (2022) - [i11]Saswat Das, Rakshit Naidu:
Fair Context-Aware Privacy Threat Modelling. CoRR abs/2207.09750 (2022) - 2021
- [i10]Aman Priyanshu, Rakshit Naidu:
FedPandemic: A Cross-Device Federated Learning Approach Towards Elementary Prognosis of Diseases During a Pandemic. CoRR abs/2104.01864 (2021) - [i9]Archit Uniyal, Rakshit Naidu, Sasikanth Kotti, Sahib Singh, Patrik Joslin Kenfack, Fatemehsadat Mireshghallah, Andrew Trask:
DP-SGD vs PATE: Which Has Less Disparate Impact on Model Accuracy? CoRR abs/2106.12576 (2021) - [i8]Rakshit Naidu, Aman Priyanshu, Aadith Kumar, Sasikanth Kotti, Haofan Wang, Fatemehsadat Mireshghallah:
When Differential Privacy Meets Interpretability: A Case Study. CoRR abs/2106.13203 (2021) - [i7]Priyam Basu, Tiasa Singha Roy, Rakshit Naidu, Zümrüt Müftüoglu, Sahib Singh, Fatemehsadat Mireshghallah:
Benchmarking Differential Privacy and Federated Learning for BERT Models. CoRR abs/2106.13973 (2021) - [i6]Rakshit Naidu, Harshita Diddee, Ajinkya Mulay, Aleti Vardhan, Krithika Ramesh, Ahmed S. Zamzam:
Towards Quantifying the Carbon Emissions of Differentially Private Machine Learning. CoRR abs/2107.06946 (2021) - [i5]Aman Priyanshu, Rakshit Naidu, Fatemehsadat Mireshghallah, Mohammad Malekzadeh:
Efficient Hyperparameter Optimization for Differentially Private Deep Learning. CoRR abs/2108.03888 (2021) - [i4]Priyam Basu, Tiasa Singha Roy, Rakshit Naidu, Zümrüt Müftüoglu:
Privacy enabled Financial Text Classification using Differential Privacy and Federated Learning. CoRR abs/2110.01643 (2021) - 2020
- [c1]Ajinkya Mulay, Gaspard Baye, Rakshit Naidu, Santiago González-Toral, Vineeth S, Tushar Semwal, Ayush Manish Agrawal:
FedPerf: A Practitioners' Guide to Performance of Federated Learning Algorithms. Preregister@NeurIPS 2020: 302-324 - [i3]Rakshit Naidu, Joy Michael:
SS-CAM: Smoothed Score-CAM for Sharper Visual Feature Localization. CoRR abs/2006.14255 (2020) - [i2]Jithin Sunny, Joel Jogy, Rohan Rout, Rakshit Naidu:
TeleVital: Enhancing the quality of contactless health assessment. CoRR abs/2007.00762 (2020) - [i1]Rakshit Naidu, Ankita Ghosh, Yash Maurya, Shamanth R. Nayak K, Soumya Snigdha Kundu:
IS-CAM: Integrated Score-CAM for axiomatic-based explanations. CoRR abs/2010.03023 (2020)
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