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regular update for pFL paper list #561

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16 changes: 13 additions & 3 deletions materials/paper_list/Personalized_FL/README.md
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## Personalized Federated Learning
This list is constantly being updated. Feel free to contribute!

### 2023
| Title | Venue | Link | Keywords | Note |
| --- | --- | --- | --- | --- |
| Personalized Federated Learning with Feature Alignment and Classifier Collaboration | ICLR | [pdf](https://openreview.net/pdf?id=SXZr8aDKia) | Collaboration | feature alignment by regularization, theoretically-guaranteed heads combination
| Test-Time Robust Personalization for Federated Learning | ICLR | [pdf](https://openreview.net/pdf?id=3aBuJEza5sq) | Test-time Robustness |
| A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy | ICLR | [pdf](https://openreview.net/pdf?id=FUiDMCr_W4o) | Statistical Estimation, Differential Privacy, Empirical/Hierarchical Bayes |
| FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification | ICLR | [pdf](https://openreview.net/pdf?id=9aokcgBVIj1) | few-shot learning, transfer learning |
| PerFedMask: Personalized Federated Learning with Optimized Masking Vectors | ICLR | [pdf](https://openreview.net/pdf?id=hxEIgUXLFF) | Masking vectors |
| The Best of Both Worlds: Accurate Global and Personalized Models through Federated Learning with Data-Free Hyper-Knowledge Distillation | ICLR | [pdf](https://openreview.net/pdf?id=29V3AWjVAFi) | Knowledge Distillation, Differential Privacy, | share means of local data representations and soft predictions; no public data

### 2022
| Title | Venue | Link | Keywords | Note |
| --- | --- | --- | --- | --- |
Expand All @@ -16,18 +26,18 @@ This list is constantly being updated. Feel free to contribute!
| Personalized Federated Learning via Variational Bayesian Inference | ICML | [pdf](https://arxiv.org/pdf/2206.07977.pdf) | Bayesian variational inference; Upper bound |
| Federated Learning with Partial Model Personalization | ICML | [pdf](https://proceedings.mlr.press/v162/pillutla22a/pillutla22a.pdf) | Partial model parameters; Transformer |
| On Bridging Generic and Personalized Federated Learning for Image Classification | ICLR | [pdf](https://arxiv.org/pdf/2107.00778) | Partial model parameters; |
| FedBABU: Toward Enhanced Representation for Federated Image Classification | ICLR | [pdf](https://openreview.net/pdf?id=HuaYQfggn5u) | Partial model parameters; |
| FedBABU: Toward Enhanced Representation for Federated Image Classification | ICLR | [pdf](https://openreview.net/pdf?id=HuaYQfggn5u) | Partial model parameters; | keep the head (classifer) unchanged during FL training, then conduct fine-tuning before inference
| Towards Personalized Federated Learning | Transactions on Neural Networks and Learning Systems | [pdf](https://arxiv.org/pdf/2103.00710)| Survey |

### 2021
| Title | Venue | Link | Keywords | Note |
| --- | --- | --- | --- | --- |
| Federated muli-task learning under a mixture of distributions | NeurIPS | [pdf](https://arxiv.org/pdf/2108.10252), [code](https://github.com/omarfoq/FedEM) | Distribution Mixture; Expectation-Maximization; FedEM |
| Parameterized Knowledge Transfer for Personalized Federated Learning | NeurIPS | [pdf](https://arxiv.org/pdf/2111.02862) | Knowledge Distillation |
| Parameterized Knowledge Transfer for Personalized Federated Learning | NeurIPS | [pdf](https://arxiv.org/pdf/2111.02862) | Knowledge Distillation | transmit only soft-predictions; public dataset required
| Personalized Federated Learning with Gaussian Processes | NeurIPS | [pdf](https://arxiv.org/pdf/2106.15482), [code](https://github.com/IdanAchituve/pFedGP) | Gaussian process; Generalization bound |
| Ditto: Fair and robust federated learning through personalization | ICML | [pdf](https://arxiv.org/pdf/2012.04221), [code](https://github.com/litian96/ditto) | Threat model; Fairness; Regularizer |
| Personalized Federated Learning using Hypernetworks | ICML | [pdf](https://arxiv.org/pdf/2103.04628), [code](https://github.com/AvivSham/pFedHN) | Hypernetwork; Client Embedding |
| Exploiting Shared Representations for Personalized Federated Learning | ICML | [pdf](https://arxiv.org/pdf/2102.07078.pdf), [code](https://github.com/lgcollins/FedRep) | Partial model parameters |
| Exploiting Shared Representations for Personalized Federated Learning | ICML | [pdf](https://arxiv.org/pdf/2102.07078.pdf), [code](https://github.com/lgcollins/FedRep) | Partial model parameters | FedRep, shared body (feature extractor), personalized head (classifier)
| Personalized Federated Learning with First Order Model Optimization | ICLR | [pdf](https://arxiv.org/pdf/2012.08565), [code](https://github.com/NVlabs/FedFomo) | Model mixture |
| FedBN: Federated Learning on Non-IID Features via Local Batch Normalization | ICLR | [pdf](https://arxiv.org/pdf/2102.07623), [code](https://github.com/med-air/FedBN) | Partial model parameters |

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