| Flower: A friendly federated learning research framework DJ Beutel, T Topal, A Mathur, X Qiu, J Fernandez-Marques, Y Gao, L Sani, ... arXiv preprint arXiv:2007.14390, 2020 | 1120 | 2020 |
| A first look into the carbon footprint of federated learning X Qiu, T Parcollet, J Fernandez-Marques, PPB de Gusmao, Y Gao, ... JMLR 24 (1-23), 2021 | 101 | 2021 |
| ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity X Qiu, J Fernandez-Marques, PPB Gusmao, Y Gao, T Parcollet, ND Lane International Conference on Learning Representations, 2021 | 75 | 2021 |
| On-device federated learning with flower A Mathur, DJ Beutel, PPB de Gusmao, J Fernandez-Marques, T Topal, ... arXiv preprint arXiv:2104.03042, 2021 | 50 | 2021 |
| Can Federated Learning Save the Planet? X Qiu, T Parcollet, D Beutel, T Topal, A Mathur, N Lane NeurIPS-Tackling Climate Change with Machine Learning, 2020 | 35 | 2020 |
| FedL2P: Federated Learning to Personalize R Lee, M Kim, D Li, X Qiu, T Hospedales, F Huszár, ND Lane Thirty-seventh Conference on Neural Information Processing Systems, 2023 | 25 | 2023 |
| Quaternion Neural Networks for Multi-channel Distant Speech Recognition X Qiu, T Parcollet, M Ravanelli, N Lane, M Morchid Interspeech 2020, 2020 | 20 | 2020 |
| Breaking physical and linguistic borders: Multilingual federated prompt tuning for low-resource languages W Zhao, Y Chen, R Lee, X Qiu, Y Gao, H Fan, ND Lane The Twelfth International Conference on Learning Representations, 2024 | 15 | 2024 |
| Gradient-less Federated Gradient Boosting Tree with Learnable Learning Rates C Ma, X Qiu, D Beutel, N Lane Proceedings of the 3rd Workshop on Machine Learning and Systems, 56-63, 2023 | 14 | 2023 |
| The Future of Large Language Model Pre-training is Federated L Sani, A Iacob, Z Cao, B Marino, Y Gao, T Paulik, W Zhao, WF Shen, ... arXiv preprint arXiv:2405.10853, 2024 | 13 | 2024 |
| Protea: Client profiling within federated systems using flower W Zhao, X Qiu, J Fernandez-Marques, PPB de Gusmão, ND Lane Proceedings of the 1st ACM Workshop on Data Privacy and Federated Learning …, 2022 | 13 | 2022 |
| FedVal: Different good or different bad in federated learning V Valadi, X Qiu, PPB de Gusmão, ND Lane, M Alibeigi 32nd USENIX Security Sypoposium, 2023 | 11 | 2023 |
| vfedsec: Efficient secure aggregation for vertical federated learning via secure layer X Qiu, H Pan, W Zhao, C Ma, Y Gao, PPB de Gusmao, ND Lane | 11* | 2023 |
| Evaluating Privacy Leakage in Split Learning X Qiu, I Leontiadis, L Melis, A Sablayrolles, P Stock arXiv preprint arXiv:2305.12997, 2023 | 6* | 2023 |
| Photon: Federated LLM Pre-Training L Sani, A Iacob, Z Cao, R Lee, B Marino, Y Gao, D Cai, Z Li, W Zhao, ... arXiv preprint arXiv:2411.02908, 2024 | 5 | 2024 |
| FLea: Addressing Data Scarcity and Label Skew in Federated Learning via Privacy-preserving Feature Augmentation T Xia, A Ghosh, X Qiu, C Mascolo arXiv preprint arXiv:2312.02327, 2024 | 5* | 2024 |
| PISTOL: Dataset Compilation Pipeline for Structural Unlearning of LLMs X Qiu, WF Shen, Y Chen, N Cancedda, P Stenetorp, ND Lane arXiv preprint arXiv:2406.16810, 2024 | 4 | 2024 |
| Sheaf HyperNetworks for Personalized Federated Learning B Nguyen, L Sani, X Qiu, P Liò, ND Lane arXiv preprint arXiv:2405.20882, 2024 | 4 | 2024 |
| High-throughput simulation of federated learning via resource-aware client placement L Sani, PPB de Gusmão, A Iacob, W Zhao, X Qiu, Y Gao, ... CoRR, 2023 | 3 | 2023 |
| DEPT: Decoupled Embeddings for Pre-training Language Models A Iacob, L Sani, M Kurmanji, WF Shen, X Qiu, D Cai, Y Gao, ND Lane arXiv preprint arXiv:2410.05021, 2024 | 1 | 2024 |
Nicholas LaneUniversity of Cambridge and Flower LabsVerified email at cam.ac.uk
