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2020 – today
- 2024
[c9]Wanru Zhao, Yihong Chen, Royson Lee, Xinchi Qiu, Yan Gao, Hongxiang Fan, Nicholas Donald Lane:
Breaking Physical and Linguistic Borders: Multilingual Federated Prompt Tuning for Low-Resource Languages. ICLR 2024- [c8]Tong Xia
, Abhirup Ghosh, Xinchi Qiu, Cecilia Mascolo:
FLea: Addressing Data Scarcity and Label Skew in Federated Learning via Privacy-preserving Feature Augmentation. KDD 2024: 3484-3494 - [i18]Xinchi Qiu, Yan Gao, Lorenzo Sani, Heng Pan, Wanru Zhao, Pedro P. B. de Gusmao, Mina Alibeigi, Alex Iacob, Nicholas D. Lane:
FedAnchor: Enhancing Federated Semi-Supervised Learning with Label Contrastive Loss for Unlabeled Clients. CoRR abs/2402.10191 (2024) - [i17]Lorenzo Sani, Alex Iacob, Zeyu Cao, Bill Marino, Yan Gao, Tomás Paulik, Wanru Zhao, William F. Shen, Preslav Aleksandrov, Xinchi Qiu, Nicholas D. Lane:
The Future of Large Language Model Pre-training is Federated. CoRR abs/2405.10853 (2024) - [i16]Bao Nguyen, Lorenzo Sani, Xinchi Qiu, Pietro Liò, Nicholas D. Lane:
Sheaf HyperNetworks for Personalized Federated Learning. CoRR abs/2405.20882 (2024) - [i15]Xinchi Qiu, William F. Shen, Yihong Chen, Nicola Cancedda, Pontus Stenetorp, Nicholas D. Lane:
PISTOL: Dataset Compilation Pipeline for Structural Unlearning of LLMs. CoRR abs/2406.16810 (2024) - 2023
- [j1]Xinchi Qiu, Titouan Parcollet, Javier Fernández-Marqués, Pedro P. B. de Gusmao, Yan Gao, Daniel J. Beutel, Taner Topal, Akhil Mathur, Nicholas D. Lane:
A First Look into the Carbon Footprint of Federated Learning. J. Mach. Learn. Res. 24: 129:1-129:23 (2023) - [c7]Chenyang Ma, Xinchi Qiu, Daniel J. Beutel, Nicholas D. Lane:
Gradient-less Federated Gradient Boosting Tree with Learnable Learning Rates. EuroMLSys@EuroSys 2023: 56-63 - [c6]Royson Lee, Minyoung Kim, Da Li, Xinchi Qiu, Timothy M. Hospedales, Ferenc Huszar, Nicholas D. Lane:
FedL2P: Federated Learning to Personalize. NeurIPS 2023 - [c5]Viktor Valadi, Xinchi Qiu, Pedro Porto Buarque de Gusmão, Nicholas D. Lane, Mina Alibeigi:
FedVal: Different good or different bad in federated learning. USENIX Security Symposium 2023: 6365-6380 - [i14]Chenyang Ma, Xinchi Qiu, Daniel J. Beutel, Nicholas D. Lane:
Gradient-less Federated Gradient Boosting Trees with Learnable Learning Rates. CoRR abs/2304.07537 (2023) - [i13]Xinchi Qiu, Heng Pan, Wanru Zhao, Chenyang Ma, Pedro Porto Buarque de Gusmão, Nicholas D. Lane:
Efficient Vertical Federated Learning with Secure Aggregation. CoRR abs/2305.11236 (2023) - [i12]Xinchi Qiu, Ilias Leontiadis, Luca Melis, Alexandre Sablayrolles, Pierre Stock:
EXACT: Extensive Attack for Split Learning. CoRR abs/2305.12997 (2023) - [i11]Xinchi Qiu, Heng Pan, Wanru Zhao, Chenyang Ma, Pedro P. B. de Gusmao, Nicholas D. Lane:
vFedSec: Efficient Secure Aggregation for Vertical Federated Learning via Secure Layer. CoRR abs/2305.16794 (2023) - [i10]Viktor Valadi, Xinchi Qiu, Pedro Porto Buarque de Gusmão, Nicholas D. Lane, Mina Alibeigi:
FedVal: Different good or different bad in federated learning. CoRR abs/2306.04040 (2023) - [i9]Lorenzo Sani, Pedro Porto Buarque de Gusmão, Alex Iacob, Wanru Zhao, Xinchi Qiu, Yan Gao, Javier Fernández-Marqués, Nicholas Donald Lane:
High-throughput Simulation of Federated Learning via Resource-Aware Client Placement. CoRR abs/2306.17453 (2023) - [i8]Royson Lee, Minyoung Kim, Da Li, Xinchi Qiu, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane:
FedL2P: Federated Learning to Personalize. CoRR abs/2310.02420 (2023) - 2022
- [c4]Wanru Zhao, Xinchi Qiu, Javier Fernández-Marqués, Pedro P. B. de Gusmao, Nicholas D. Lane:
Protea: client profiling within federated systems using flower. FedEdge@MobiCom 2022: 1-6 - [c3]Xinchi Qiu, Javier Fernández-Marqués, Pedro P. B. de Gusmao, Yan Gao, Titouan Parcollet, Nicholas Donald Lane:
ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity. ICLR 2022 - [i7]Wanru Zhao, Xinchi Qiu, Javier Fernández-Marqués, Pedro Porto Buarque de Gusmão, Nicholas D. Lane:
Protea: Client Profiling within Federated Systems using Flower. CoRR abs/2207.01053 (2022) - [i6]Xinchi Qiu, Javier Fernández-Marqués, Pedro Porto Buarque de Gusmão, Yan Gao, Titouan Parcollet, Nicholas Donald Lane:
ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity. CoRR abs/2208.02507 (2022) - 2021
- [i5]Xinchi Qiu, Titouan Parcollet, Javier Fernández-Marqués, Pedro Porto Buarque de Gusmão, Daniel J. Beutel, Taner Topal, Akhil Mathur, Nicholas D. Lane:
A first look into the carbon footprint of federated learning. CoRR abs/2102.07627 (2021) - [i4]Akhil Mathur, Daniel J. Beutel, Pedro Porto Buarque de Gusmão, Javier Fernández-Marqués, Taner Topal, Xinchi Qiu, Titouan Parcollet, Yan Gao, Nicholas D. Lane:
On-device Federated Learning with Flower. CoRR abs/2104.03042 (2021) - 2020
- [c2]Xinchi Qiu, Titouan Parcollet, Mirco Ravanelli, Nicholas D. Lane, Mohamed Morchid:
Quaternion Neural Networks for Multi-Channel Distant Speech Recognition. INTERSPEECH 2020: 329-333 - [c1]Titouan Parcollet, Xinchi Qiu, Nicholas D. Lane:
FusionRNN: Shared Neural Parameters for Multi-Channel Distant Speech Recognition. INTERSPEECH 2020: 1678-1682 - [i3]Xinchi Qiu, Titouan Parcollet, Mirco Ravanelli, Nicholas D. Lane, Mohamed Morchid:
Quaternion Neural Networks for Multi-channel Distant Speech Recognition. CoRR abs/2005.08566 (2020) - [i2]Daniel J. Beutel, Taner Topal, Akhil Mathur, Xinchi Qiu, Titouan Parcollet, Nicholas D. Lane:
Flower: A Friendly Federated Learning Research Framework. CoRR abs/2007.14390 (2020) - [i1]Xinchi Qiu, Titouan Parcollet, Daniel J. Beutel, Taner Topal, Akhil Mathur, Nicholas D. Lane:
A first look into the carbon footprint of federated learning. CoRR abs/2010.06537 (2020)
Coauthor Index
aka: Pedro P. B. de Gusmao
aka: Nicholas Donald Lane
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