no code implementations • 17 Dec 2023 • Daniel Gerbi Duguma, Juliana Zhang, Meysam Aboutalebi, Shiliang Zhang, Catherine Banet, Cato Bjørkli, Chinmayi Baramashetru, Frank Eliassen, HUI ZHANG, Jonathan Muringani, Josef Noll, Knut Inge Fostervold, Lars Böcker, Lee Andrew Bygrave, Matin Bagherpour, Maunya Doroudi Moghadam, Olaf Owe, Poushali Sengupta, Roman Vitenberg, Sabita Maharjan, Thiago Garrett, Yushuai Li, Zhengyu Shan
This manuscript aims to formalize and conclude the discussions initiated during the PriTEM workshop 22-23 March 2023.
no code implementations • 23 May 2023 • Poushali Sengupta, Yan Zhang, Sabita Maharjan, Frank Eliassen
Furthermore, we provide an upper bound of the computation complexity of our proposed approach for the dependent features.
Autonomous Driving Explainable Artificial Intelligence (XAI)
1 code implementation • 13 Sep 2020 • Sudipta Paul, Poushali Sengupta, Subhankar Mishra
FL uses the FedAvg algorithm, which is trained in the iterative model averaging way, on the non-iid and unbalanced distributed data, without depending on the data quantity.
no code implementations • 10 Jun 2020 • Poushali Sengupta, Sudipta Paul, Subhankar Mishra
The different aspects of differential privacy, it's application in privacy protection and leakage of information, a comparative discussion, on the current research approaches in this field, its utility in the real world as well as the trade-offs - will be discussed.
no code implementations • 7 Jun 2020 • Poushali Sengupta, Sudipta Paul, Subhankar Mishra
In this work, after collecting one-hot encoded data from different sources and clients, a step of novel attribute shuffling technique using iterative shuffling (based on the query asked by the analyst) and loss estimation with an updation function and risk minimization produces a utility and privacy balanced differential private report.