Kritika Prakash
Kritika Prakash
Microsoft Research
Verified email at - Homepage
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Pysyft: A library for easy federated learning
A Ziller, A Trask, A Lopardo, B Szymkow, B Wagner, E Bluemke, ...
Federated Learning Systems: Towards Next-Generation AI, 111-139, 2021
Syft 0.5: A platform for universally deployable structured transparency
AJ Hall, M Jay, T Cebere, B Cebere, KL van der Veen, G Muraru, T Xu, ...
arXiv preprint arXiv:2104.12385, 2021
How private is your RL policy? An inverse RL based analysis framework
K Prakash, F Husain, P Paruchuri, S Gujar
Proceedings of the AAAI Conference on Artificial Intelligence 36 (7), 8009-8016, 2022
VidyutVanika: An Autonomous Broker Agent for Smart Grid Environment
S Ghosh, K Prakash, S Chandlekar, E Subramanian, S Bhat, S Gujar, ...
Policy, Awareness, Sustainability and Systems Workshop, 5, 2019
ADVISER: AI-Driven vaccination intervention optimiser for increasing vaccine uptake in Nigeria
V Nair, K Prakash, M Wilbur, A Taneja, C Namblard, O Adeyemo, A Dubey, ...
arXiv preprint arXiv:2204.13663, 2022
Sensitivity analysis in differentially private machine learning using hybrid automatic differentiation
A Ziller, D Usynin, M Knolle, K Prakash, A Trask, R Braren, M Makowski, ...
arXiv preprint arXiv:2107.04265, 2021
PredictRV: A Prediction Based Strategy for Negotiations with Dynamically Changing Reservation Value
AS Gear, K Prakash, N Singh, P Paruchuri
International Conference on Group Decision and Negotiation, 135-148, 2020
An automatic differentiation system for the age of differential privacy
D Usynin, A Ziller, M Knolle, A Trask, K Prakash, D Rueckert, G Kaissis
arXiv preprint arXiv:2109.10573, 2021
Towards General-purpose Infrastructure for Protecting Scientific Data Under Study
A Trask, K Prakash
Privacy Preserving Machine Learning - NeurIPS 2020, 4, 2020
Privacy Attacks in Reinforcement Learning with Sensitive Rewards
K Prakash
International Institute of Information Technology, Hyderabad, 2022
Privacy Preserving Machine Learning, A Survey
K Prakash, S Gujar
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