| 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)@conference{Samhita22a,
title = {Fair Federated Learning for Heterogeneous Data},
author = {Samhita Kanaparthy and Manisha Padala and Sankarshan Damle and Sujit Gujar},
year = {2022},
date = {2022-01-05},
booktitle = {Young Researchers Symposium, CODS-COMAD'22.},
keywords = {fairness, federated learning},
pubstate = {forthcoming},
tppubtype = {conference}
}
|
| 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)@conference{Padala2021b,
title = {Learning Equilibrium Contributions in Multi-project Civic Crowdfunding},
author = {Manisha Padala and Sankarshan Damle and Sujit Gujar},
year = {2021},
date = {2021-12-14},
booktitle = {To Appear in the Proceeding of The 20th IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT '21)},
keywords = {Civic Crowdfunding, Mechanism Design, Reinforcement Learning},
pubstate = {forthcoming},
tppubtype = {conference}
}
|
| 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)@conference{Padala2021c,
title = {Mechanism Design without Money for Fair Allocations},
author = {Manisha Padala and Sujit Gujar},
year = {2021},
date = {2021-12-14},
booktitle = {To Appear in the proceedings of the 20th IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology 2021 (WI-IAT '21).},
keywords = {fairness, Mechanism Design},
pubstate = {forthcoming},
tppubtype = {conference}
}
|
| 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)@inproceedings{Padala2021,
title = {Effect of Input Noise Dimension in GANs},
author = {Manisha Padala and Debojit Das and Sujit Gujar
},
year = {2021},
date = {2021-12-08},
booktitle = {Proceedings 28th International Conference on Neural Information Processing (ICONIP) of the Asia-Pacific Neural Network Society 2021 (ICONIP '21)},
keywords = {GAN, Machine Learning},
pubstate = {forthcoming},
tppubtype = {inproceedings}
}
|
| 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)@inproceedings{Manisha2021b,
title = {Federated Learning Meets Fairness and Differential Privacy},
author = {Manisha Padala and Sankarshan Damle, and Sujit Gujar},
year = {2021},
date = {2021-12-08},
publisher = {Proceedings of the 28th International Conference on Neural Information Processing (ICONIP) of the Asia-Pacific Neural Network Society 2021 (ICONIP '21)},
keywords = {differential privacy, fairness, federated learning},
pubstate = {forthcoming},
tppubtype = {inproceedings}
}
|
