ICML 2023 Workshop FL Submissions

On the Still Unreasonable Effectiveness of Federated Averaging for Heterogeneous Distributed Learning
Kumar Kshitij Patel, Margalit Glasgow, Lingxiao Wang, Nirmit Joshi, Nathan Srebro
- Published: 19 Jun 2023, Last Modified: 21 Jul 2023
- FL-ICML 2023
- Readers: Everyone
Towards a Theoretical and Practical Understanding of One-Shot Federated Learning with Fisher Information
Divyansh Jhunjhunwala, Shiqiang Wang, Gauri Joshi
- Published: 19 Jun 2023, Last Modified: 21 Jul 2023
- FL-ICML 2023
- Readers: Everyone
Machine Learning with Feature Differential Privacy
Saeed Mahloujifar, Chuan Guo, G. Edward Suh, Kamalika Chaudhuri
- Published: 19 Jun 2023, Last Modified: 21 Jul 2023
- FL-ICML 2023
- Readers: Everyone
Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning
Kostadin Garov, Dimitar Iliev Dimitrov, Nikola Jovanović, Martin Vechev
- Published: 19 Jun 2023, Last Modified: 23 Jul 2023
- FL-ICML 2023
- Readers: Everyone
Beyond Secure Aggregation: Scalable Multi-Round Secure Collaborative Learning
Umit Yigit Basaran, Xingyu Lu, Basak Guler
- Published: 19 Jun 2023, Last Modified: 21 Jul 2023
- FL-ICML 2023
- Readers: Everyone
Federated Experiment Design under Distributed Differential Privacy
Wei-Ning Chen, Graham Cormode, Akash Bharadwaj, Peter Romov, Ayfer Ozgur
- Published: 19 Jun 2023, Last Modified: 21 Jul 2023
- FL-ICML 2023
- Readers: Everyone
FedFwd: Federated Learning without Backpropagation
Seonghwan Park, Dahun Shin, Jinseok Chung, Namhoon Lee
- Published: 19 Jun 2023, Last Modified: 21 Jul 2023
- FL-ICML 2023
- Readers: Everyone
Unleashing the Power of Randomization in Auditing Differentially Private ML
Krishna Pillutla, Galen Andrew, Peter Kairouz, Hugh Brendan McMahan, Alina Oprea, Sewoong Oh
- Published: 19 Jun 2023, Last Modified: 21 Jul 2023
- FL-ICML 2023
- Readers: Everyone
Demystifying Local and Global Fairness Trade-offs in Federated Learning Using Information Theory
Faisal Hamman, Sanghamitra Dutta
- Published: 19 Jun 2023, Last Modified: 21 Jul 2023
- FL-ICML 2023
- Readers: Everyone
Fast and Communication Efficient Decentralized Learning with Local Updates
Peyman Gholami, Hulya Seferoglu
- Published: 19 Jun 2023, Last Modified: 21 Jul 2023
- FL-ICML 2023
- Readers: Everyone
Re-Weighted Softmax Cross-Entropy to Control Forgetting in Federated Learning
Gwen Legate, Lucas Caccia, Eugene Belilovsky
- Published: 19 Jun 2023, Last Modified: 21 Jul 2023
- FL-ICML 2023
- Readers: Everyone
Tackling the Data Heterogeneity in Asynchronous Federated Learning with Cached Update Calibration
Yujia Wang, Yuanpu Cao, Jingcheng Wu, Ruoyu Chen, Jinghui Chen
- Published: 19 Jun 2023, Last Modified: 21 Jul 2023
- FL-ICML 2023
- Readers: Everyone
Privacy Amplification via Compression: Achieving the Optimal Privacy-Accuracy-Communication Trade-off in Distributed Mean Estimation
Wei-Ning Chen, Dan Song, Ayfer Ozgur, Peter Kairouz
- Published: 19 Jun 2023, Last Modified: 21 Jul 2023
- FL-ICML 2023
- Readers: Everyone
FedSelect: Customized Selection of Parameters for Fine-Tuning during Personalized Federated Learning
Rishub Tamirisa, John Won, Chengjun Lu, Ron Arel, Andy Zhou
- Published: 19 Jun 2023, Last Modified: 21 Jul 2023
- FL-ICML 2023
- Readers: Everyone
A New Theoretical Perspective on Data Heterogeneity in Federated Optimization
Jiayi Wang, Shiqiang Wang, Rong-Rong Chen, Mingyue Ji
- Published: 19 Jun 2023, Last Modified: 21 Jul 2023
- FL-ICML 2023
- Readers: Everyone
Don’t Memorize; Mimic The Past: Federated Class Incremental Learning Without Episodic Memory
Sara Babakniya, Zalan Fabian, Chaoyang He, Mahdi Soltanolkotabi, Salman Avestimehr
- Published: 19 Jun 2023, Last Modified: 21 Jul 2023
- FL-ICML 2023
- Readers: Everyone
Fed-CPrompt: Contrastive Prompt for Rehearsal-Free Federated Continual Learning
Gaurav Bagwe, Xiaoyong Yuan, Miao Pan, Lan Zhang
- Published: 19 Jun 2023, Last Modified: 21 Jul 2023
- FL-ICML 2023
- Readers: Everyone
Improving Accelerated Federated Learning with Compression and Importance Sampling
Michał Grudzień, Grigory Malinovsky, Peter Richtárik
- Published: 19 Jun 2023, Last Modified: 21 Jul 2023
- FL-ICML 2023
- Readers: Everyone
Federated Heavy Hitter Recovery under Linear Sketching
Adria Gascon, Peter Kairouz, Ziteng Sun, Ananda Theertha Suresh
- Published: 19 Jun 2023, Last Modified: 21 Jul 2023
- FL-ICML 2023
- Readers: Everyone
Exact Optimality in Communication-Privacy-Utility Tradeoffs
Berivan Isik, Wei-Ning Chen, Ayfer Ozgur, Tsachy Weissman, Albert No
- Published: 19 Jun 2023, Last Modified: 21 Jul 2023
- FL-ICML 2023
- Readers: Everyone
Guiding The Last Layer in Federated Learning with Pre-Trained Models
Gwen Legate, Nicolas Bernier, Lucas Caccia, Edouard Oyallon, Eugene Belilovsky
- Published: 19 Jun 2023, Last Modified: 21 Jul 2023
- FL-ICML 2023
- Readers: Everyone
Green Federated Learning
Ashkan Yousefpour, Shen Guo, Ashish Shenoy, Sayan Ghosh, Pierre Stock, Kiwan Maeng, Schalk-Willem Krüger, Michael Rabbat, Carole-Jean Wu, Ilya Mironov
- Published: 19 Jun 2023, Last Modified: 21 Jul 2023
- FL-ICML 2023
- Readers: Everyone
Adaptive Federated Learning with Auto-Tuned Clients via Local Smoothness
Junhyung Lyle Kim, Taha Toghani, Cesar A Uribe, Anastasios Kyrillidis
- Published: 19 Jun 2023, Last Modified: 21 Jul 2023
- FL-ICML 2023
- Readers: Everyone
Federated, Fast, and Private Visualization of Decentralized Data
Debbrata Kumar Saha, Vince Calhoun, Soo Min Kwon, Anand Sarwate, Rekha Saha, Sergey Plis
- Published: 19 Jun 2023, Last Modified: 21 Jul 2023
- FL-ICML 2023
- Readers: Everyone
Private Federated Learning with Dynamic Power Control via Non-Coherent Over-the-Air Computation
Anbang Zhang, Shuaishuai Guo, Shuai Liu
- Published: 19 Jun 2023, Last Modified: 26 Jul 2023
- FL-ICML 2023
- Readers: Everyone