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; Sujit Gujar: Mechanism Design without Money for Fair Allocations. To Appear in the proceedings of the 20th IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology 2021 (WI-IAT '21)., Forthcoming. (Type: Conference | BibTeX | Tags: fairness, Mechanism Design)
4.Manisha Padala; Debojit Das; Sujit Gujar: Effect of Input Noise Dimension in GANs. In: Proceedings 28th International Conference on Neural Information Processing (ICONIP) of the Asia-Pacific Neural Network Society 2021 (ICONIP '21), Forthcoming. (Type: Conference | BibTeX | Tags: GAN, Machine Learning)
5.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)