| 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 | 773 | 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 | 70 | 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 | 54 | 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 | 40 | 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 | 27 | 2020 |
| Quaternion Neural Networks for Multi-channel Distant Speech Recognition X Qiu, T Parcollet, M Ravanelli, N Lane, M Morchid Interspeech 2020, 2020 | 16 | 2020 |
| 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 | 9 | 2023 |
| 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 | 8 | 2022 |
| 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 | 7 | 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 | 7* | 2023 |
| 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 | 6 | 2024 |
| 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 | 4 | 2023 |
| EXACT: Extensive Attack for Split Learning X Qiu, I Leontiadis, L Melis, A Sablayrolles, P Stock arXiv preprint arXiv:2305.12997, 2023 | 4 | 2023 |
| Sheaf HyperNetworks for Personalized Federated Learning B Nguyen, L Sani, X Qiu, P Liò, ND Lane arXiv preprint arXiv:2405.20882, 2024 | 1 | 2024 |
| 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 | 1 | 2024 |
| FusionRNN: Shared Neural Parameters for Multi-Channel Distant Speech Recognition T Parcollet, X Qiu, N Lane Interspeech 2020, 1678-1682, 2020 | 1 | 2020 |
| 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 | | 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:2406.09547, 2024 | | 2024 |
| FedAnchor: Enhancing Federated Semi-Supervised Learning with Label Contrastive Loss for Unlabeled Clients X Qiu, Y Gao, L Sani, H Pan, W Zhao, PPB Gusmao, M Alibeigi, A Iacob, ... arXiv preprint arXiv:2402.10191, 2024 | | 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, ... arXiv preprint arXiv:2306.17453, 2023 | | 2023 |
Nicholas LaneUniversity of Cambridge and Flower LabsVerified email at cam.ac.uk
