1.Samhita Kanaparthy; Manisha Padala; Sankarshan Damle; Sujit Gujar: Fair Federated Learning for Heterogeneous Data. Young Researchers Symposium, CODS-COMAD'22., Forthcoming. (Type: Conference | BibTeX | Tags: fairness, federated learning)
2.Manisha Padala; Sankarshan Damle; Sujit Gujar: Learning Equilibrium Contributions in Multi-project Civic Crowdfunding. To Appear in the Proceeding of The 20th IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT '21), Forthcoming. (Type: Conference | BibTeX | Tags: Civic Crowdfunding, Mechanism Design, Reinforcement Learning)
3.Manisha Padala; Sankarshan Damle ; Sujit Gujar: Federated Learning Meets Fairness and Differential Privacy. In: Proceedings of the 28th International Conference on Neural Information Processing (ICONIP) of the Asia-Pacific Neural Network Society 2021 (ICONIP '21), Forthcoming. (Type: Conference | BibTeX | Tags: differential privacy, fairness, federated learning)
4.Padala Manisha; Sankarshan Damle; Sujit Gujar: Building Ethical AI: Federated Learning meets Fairness and Privacy. First Indian Conference on Deployable AI, 2021. (Type: Conference | BibTeX | Tags: differential privacy, fairness, federated learning)
5.Sanidhay Arora; Anurag Jain; Sankarshan Damle; Sujit Gujar: ASHWAChain: A Fast, Scalable and Strategy-proof Committee-based Blockchain Protocol. Workshop on Game Theory in Blockchain at WINE 2020 (GTiB@WINE 2020), 2020. (Type: Workshop | BibTeX | Tags: Blockchain, Blockchain Consensus Protocols, Game Theory, Scalable Blockchain)