论文整理 | ICLR 2023 联邦学习论文合集

国际表征学习大会（International Conference on Learning Representations，简称 ICLR）是深度学习领域的顶级会议，关注有关深度学习各个方面的前沿研究，在人工智能、统计和数据科学领域以及机器视觉、语音识别、文本理解等重要应用领域中发布了众多极其有影响力的论文。

通过AI技术对 ICLR2023 收录的会议论文进行了分类整理，其中关于联邦学习的论文有34篇。本文将罗列这34篇论文，感兴趣的小伙伴可以访问论文下方的链接阅读原文~

• Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning

Yujun Shi, Jian Liang, Wenqing Zhang, Vincent Tan, Song Bai

https://openreview.net/forum?id=EXnIyMVTL8s

• Personalized Federated Learning with Feature Alignment and Classifier Collaboration

Jian Xu, Xinyi Tong, Shao-Lun Huang

https://openreview.net/forum?id=SXZr8aDKia

• The Best of Both Worlds: Accurate Global and Personalized Models through Federated Learning with Data-Free Hyper-Knowledge Distillation

Huancheng Chen, Chaining Wang, Haris Vikalo

https://openreview.net/forum?id=29V3AWjVAFi

• Towards Addressing Label Skews in One-Shot Federated Learning

Yiqun Diao, Qinbin Li, Bingsheng He

https://openreview.net/forum?id=rzrqh85f4Sc

• FedSpeed: Larger Local Interval, Less Communication Round, and Higher Generalization Accuracy

Yan Sun, Li Shen, Tiansheng Huang, Liang Ding, Dacheng Tao

https://openreview.net/forum?id=bZjxxYURKT

• Generalization Bounds for Federated Learning: Fast Rates, Unparticipating Clients and Unbounded Losses

Xiaolin Hu, Shaojie Li, Yong Liu

https://openreview.net/forum?id=-EHqoysUYLx

• Better Generative Replay for Continual Federated Learning

Daiqing Qi, Handong Zhao, Sheng Li

https://openreview.net/forum?id=cRxYWKiTan

• Federated Learning from Small Datasets

Michael Kamp, Jonas Fischer, Jilles Vreeken

https://openreview.net/forum?id=hDDV1lsRV8

• FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification

Aliaksandra Shysheya, John F Bronskill, Massimiliano Patacchiola, Sebastian Nowozin, Richard E Turner

https://openreview.net/forum?id=9aokcgBVIj1

• Federated Nearest Neighbor Machine Translation

Yichao Du, Zhirui Zhang, Bingzhe Wu, Lemao Liu, Tong Xu, Enhong Chen

https://openreview.net/forum?id=R1U5G2spbLd

• On the Importance and Applicability of Pre-Training for Federated Learning

Hong-You Chen, Cheng-Hao Tu, Ziwei Li, Han Wei Shen, Wei-Lun Chao

https://openreview.net/forum?id=fWWFv--P0xP

• SWIFT: Rapid Decentralized Federated Learning via Wait-Free Model Communication

Marco Bornstein, Tahseen Rabbani, Evan Z Wang, Amrit Bedi, Furong Huang

https://openreview.net/forum?id=jh1nCir1R3d

• Does Decentralized Learning with Non-IID Unlabeled Data Benefit from Self Supervision?

Lirui Wang, Kaiqing Zhang, Yunzhu Li, Yonglong Tian, Russ Tedrake

https://openreview.net/forum?id=2L9gzS80tA4

• FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning

Kaiyuan Zhang, Guanhong Tao, Qiuling Xu, Siyuan Cheng, Shengwei An, Yingqi Liu, Shiwei Feng, Guangyu Shen, Pin-Yu Chen, Shiqing Ma, Xiangyu Zhang

https://openreview.net/forum?id=Xo2E217_M4n

• Faster federated optimization under second-order similarity

Ahmed Khaled, Chi Jin

https://openreview.net/forum?id=ElC6LYO4MfD

• FedFA: Federated Feature Augmentation

Tianfei Zhou, Ender Konukoglu

https://openreview.net/forum?id=U9yFP90jU0

• FedExP: Speeding up Federated Averaging via Extrapolation

Divyansh Jhunjhunwala, Shiqiang Wang, Gauri Joshi

https://openreview.net/forum?id=IPrzNbddXV

• DepthFL : Depthwise Federated Learning for Heterogeneous Clients

Minjae Kim, Sangyoon Yu, Suhyun Kim, Soo-Mook Moon

https://openreview.net/forum?id=pf8RIZTMU58

• Test-Time Robust Personalization for Federated Learning

Liangze Jiang, Tao Lin

https://openreview.net/forum?id=3aBuJEza5sq

• FedDAR: Federated Domain-Aware Representation Learning

Aoxiao Zhong, Hao He, Zhaolin Ren, Na Li, Quanzheng Li

https://openreview.net/forum?id=6P9Y25Pljl6

• Machine Unlearning of Federated Clusters

Chao Pan, Jin Sima, Saurav Prakash, Vishal Rana, Olgica Milenkovic

https://openreview.net/forum?id=VzwfoFyYDga

• Effective passive membership inference attacks in federated learning against overparameterized models

Jiacheng Li, Ninghui Li, Bruno Ribeiro

https://openreview.net/forum?id=QsCSLPP55Ku

• Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models

Liam H Fowl, Jonas Geiping, Steven Reich, Yuxin Wen, Wojciech Czaja, Micah Goldblum, Tom Goldstein

https://openreview.net/forum?id=r0BrY4BiEXO

• Where to Begin? Exploring the Impact of Pre-Training and Initialization in Federated

John Nguyen, Jianyu Wang, Kshitiz Malik, Maziar Sanjabi, Michael Rabbat

https://openreview.net/forum?id=Mpa3tRJFBb

• Share Your Representation Only: Guaranteed Improvement of the Privacy-Utility Tradeoff in Federated Learning

Zebang Shen, Jiayuan Ye, Anmin Kang, Hamed Hassani, Reza Shokri

https://openreview.net/forum?id=oJpVVGXu9i

• Panning for Gold in Federated Learning: Targeted Text Extraction under Arbitrarily Large-Scale Aggregation

Hong-Min Chu, Jonas Geiping, Liam H Fowl, Micah Goldblum, Tom Goldstein

https://openreview.net/forum?id=A9WQaxYsfx

• EPISODE: Episodic Gradient Clipping with Periodic Resampled Corrections for Federated Learning with Heterogeneous Data

Michael Crawshaw, Yajie Bao, Mingrui Liu

https://openreview.net/forum?id=ytZIYmztET

• Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback

Boxin Zhao, Ziqi Liu, Chaochao Chen, mladen kolar, Zhiqiang Zhang, JUN ZHOU

https://openreview.net/forum?id=f3dqV4KLZV1

• Turning the Curse of Heterogeneity in Federated Learning into a Blessing for Out-of-Distribution Detection

Shuyang Yu, Junyuan Hong, Haotao Wang, Zhangyang Wang, Jiayu Zhou

https://openreview.net/forum?id=mMNimwRb7Gr

• Single-shot General Hyper-parameter Optimization for Federated Learning

Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig

https://openreview.net/forum?id=3RhuF8foyPW

• CANIFE: Crafting Canaries for Empirical Privacy Measurement in Federated Learning

Samuel Maddock, Alexandre Sablayrolles, Pierre Stock

https://openreview.net/forum?id=Kf7Yyf4O0u

• Hyperparameter Optimization through Neural Network Partitioning

Bruno Kacper Mlodozeniec, Matthias Reisser, Christos Louizos

https://openreview.net/forum?id=nAgdXgfmqj

• Instance-wise Batch Label Restoration via Gradients in Federated Learning

Kailang Ma, Yu Sun, Jian Cui, Dawei Li, Zhenyu Guan, Jianwei Liu

https://openreview.net/forum?id=FIrQfNSOoTr

• Private Federated Learning Without a Trusted Server: Optimal Algorithms for Convex Losses

Andrew Lowy, Meisam Razaviyayn

https://openreview.net/forum?id=TVY6GoURrw

本文参考：AI TIME 论道

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