87 lines
6.1 KiB
Markdown
87 lines
6.1 KiB
Markdown
# Fairness in Federated Learning
|
|
|
|
|
|
## Fairness - Demographic Disparity
|
|
### 2022
|
|
| Title | Venue | Link
|
|
| ------------------------------------------------------------ | ---------- |---------------------------------------------
|
|
| Privfairfl: Privacy-preserving group fairness in federated learning | arxiv | [pdf](https://arxiv.org/pdf/2205.11584v1.pdf)
|
|
| Fair federated learning for heterogeneous data | IKDD CODS & COMAD | [pdf](https://dl.acm.org/doi/fullHtml/10.1145/3493700.3493750)
|
|
|FairVFL: A Fair Vertical Federated Learning Framework with Contrastive Adversarial Learning| NeurIPS| [pdf](https://openreview.net/pdf?id=5vVSA_cdRqe)
|
|
|
|
### 2021
|
|
| Title | Venue | Link
|
|
| ------------------------------------------------------------ | ---------- |---------------------------------------------
|
|
| Addressing algorithmic disparity and performance inconsistency in federated learning| NeurIPS Workshop| [pdf](https://arxiv.org/pdf/2108.08435.pdf)|
|
|
|Enforcing fairness in private federated learning via the modified method of differential multipliers| NeurIPS Workshop| [pdf](https://arxiv.org/abs/2109.08604)|
|
|
| Fairness-aware agnostic federated learning | SDM|[pdf](https://arxiv.org/pdf/2010.05057.pdf)|
|
|
| Federated adversarial debiasing for fair and transferable representations| KDD| [pdf](https://dl.acm.org/doi/pdf/10.1145/3447548.3467281)|
|
|
|
|
|
|
### 2019
|
|
| Title | Venue | Link
|
|
| ------------------------------------------------------------ | ---------- |---------------------------------------------
|
|
|Agnostic federated learning | ICML| [pdf](http://proceedings.mlr.press/v97/mohri19a/mohri19a.pdf)|
|
|
|
|
|
|
## Fairness - Client performance parity
|
|
|
|
### Survey
|
|
| Title | Venue | Link
|
|
| ------------------------------------------------------------ | ---------- |---------------------------------------------
|
|
|Non-iid data and continual learning processes in federated learning: A long road ahead| Information Fution| [pdf](https://arxiv.org/pdf/2111.13394.pdf)
|
|
|Federated learning on non-iid data silos: An experimental study | ICDE|[pdf](https://arxiv.org/pdf/2102.02079.pdf)
|
|
|Federated learning on non-iid data: A survey | Neurocomputing | [pdf](https://arxiv.org/pdf/2106.06843.pdf)
|
|
|
|
|
|
### 2022
|
|
| Title | Venue | Link
|
|
| ------------------------------------------------------------ | ---------- |---------------------------------------------
|
|
|Fedmgda+: Federated learning meets multi-objective optimization | IEEE Transactions on Network Science and Engineering| [pdf](https://arxiv.org/pdf/2006.11489.pdf)
|
|
|Fairness in Federated Learning via Core-Stability | NeurIPS | [pdf](https://openreview.net/pdf?id=lKULHf7oFDo)
|
|
|
|
### 2021
|
|
| Title | Venue | Link
|
|
| ------------------------------------------------------------ | ---------- |---------------------------------------------
|
|
|Ditto: Fair and robust federated learning through personalization| ICML | [pdf](http://proceedings.mlr.press/v139/li21h/li21h.pdf)
|
|
|
|
|
|
### 2020
|
|
| Title | Venue | Link
|
|
| ------------------------------------------------------------ | ---------- |---------------------------------------------
|
|
|Federated optimization in heterogeneous networks| ICML| [pdf](https://arxiv.org/pdf/1812.06127.pdf)
|
|
|Fair resource allocation in federated learning | ICLR | [pdf](https://arxiv.org/pdf/1905.10497.pdf)
|
|
| Scaffold: Stochastic controlled averaging for federated learning| ICML | [pdf](https://arxiv.org/pdf/1910.06378.pdf)
|
|
|
|
|
|
## Fairness - Collaborative fairness
|
|
|
|
### Survey
|
|
| Title | Venue | Link
|
|
| ------------------------------------------------------------ | ---------- |---------------------------------------------
|
|
|A comprehensive survey of incentive mechanism for federated learning| arXiv | [pdf](https://arxiv.org/pdf/2106.15406.pdf)
|
|
|
|
|
|
### 2022
|
|
| Title | Venue | Link
|
|
| ------------------------------------------------------------ | ---------- |---------------------------------------------
|
|
|Collaboration equilibrium in federated learning| KDD | [pdf](https://arxiv.org/pdf/2108.07926.pdf)
|
|
| Fedfaim: A model performance-based fair incentive mechanism for federated learning| IEEE Transactionson Big Data| [pdf](https://ieeexplore.ieee.org/document/9797864)
|
|
|
|
|
|
|
|
### 2021
|
|
| Title | Venue | Link
|
|
| ------------------------------------------------------------ | ---------- |---------------------------------------------
|
|
|Incentive mechanism for horizontal federated learning based on reputation and reverse auction | WWW | [pdf](https://dl.acm.org/doi/10.1145/3442381.3449888)
|
|
| One for one, or all for all: Equilibria and optimality of collaboration in federated learning | ICML | [pdf](https://arxiv.org/pdf/2103.03228.pdf)
|
|
|
|
|
|
### 2020
|
|
| Title | Venue | Link
|
|
| ------------------------------------------------------------ | ---------- |---------------------------------------------
|
|
|A fairness-aware incentive scheme for federated learning| AIES | [pdf](https://dl.acm.org/doi/10.1145/3375627.3375840)
|
|
| Collaborative fairness in federated learning | Federated Learning | [pdf](https://arxiv.org/pdf/2008.12161.pdf)
|
|
| Towards fair and privacy-preserving federated deep models | IEEE TPDS | [pdf](https://arxiv.org/pdf/1906.01167.pdf)
|
|
|