Xinchi Qiu

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 28

Top Topics

Uniform Convergence

Unlabeled Samples

Top Venues

USENIX Security Symposium

Publications

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 (2024)
Bao Nguyen, Lorenzo Sani, Xinchi Qiu, Pietro Liò, Nicholas D. Lane
Sheaf HyperNetworks for Personalized Federated Learning. CoRR (2024)
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 (2024)
Xinchi Qiu, William F. Shen, Yihong Chen, Nicola Cancedda, Pontus Stenetorp, Nicholas D. Lane
PISTOL: Dataset Compilation Pipeline for Structural Unlearning of LLMs. CoRR (2024)
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)
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)
Royson Lee, Minyoung Kim, Da Li, Xinchi Qiu, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane
FedL2P: Federated Learning to Personalize. CoRR (2023)
Xinchi Qiu, Heng Pan, Wanru Zhao, Chenyang Ma, Pedro Porto Buarque de Gusmão, Nicholas D. Lane
Efficient Vertical Federated Learning with Secure Aggregation. CoRR (2023)
Chenyang Ma, Xinchi Qiu, Daniel J. Beutel, Nicholas D. Lane
Gradient-less Federated Gradient Boosting Trees with Learnable Learning Rates. CoRR (2023)
Royson Lee, Minyoung Kim, Da Li, Xinchi Qiu, Timothy M. Hospedales, Ferenc Huszar, Nicholas D. Lane
FedL2P: Federated Learning to Personalize. NeurIPS (2023)
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 (2023)
Xinchi Qiu, Ilias Leontiadis, Luca Melis, Alexandre Sablayrolles, Pierre Stock
EXACT: Extensive Attack for Split Learning. CoRR (2023)
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)
Chenyang Ma, Xinchi Qiu, Daniel J. Beutel, Nicholas D. Lane
Gradient-less Federated Gradient Boosting Tree with Learnable Learning Rates. EuroMLSys@EuroSys (2023)
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 (2023)
Lorenzo Sani, Pedro Porto Buarque de Gusmão, Alex Iacob, Wanru Zhao, Xinchi Qiu, Yan Gao, Javier Fernández-Marquás, Nicholas Donald Lane
High-throughput Simulation of Federated Learning via Resource-Aware Client Placement. CoRR (2023)
Viktor Valadi, Xinchi Qiu, Pedro Porto Buarque de Gusmão, Nicholas D. Lane, Mina Alibeigi
FedVal: Different good or different bad in federated learning. CoRR (2023)
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 (2022)
Xinchi Qiu, Javier Fernández-Marqués, Pedro P. B. Gusmao, Yan Gao, Titouan Parcollet, Nicholas Donald Lane
ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity. ICLR (2022)
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)
Wanru Zhao, Xinchi Qiu, Javier Fernández-Marqués, Pedro Porto Buarque de Gusmão, Nicholas D. Lane
Protea: Client Profiling within Federated Systems using Flower. CoRR (2022)
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 (2021)
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 (2021)
Titouan Parcollet, Xinchi Qiu, Nicholas D. Lane
FusionRNN: Shared Neural Parameters for Multi-Channel Distant Speech Recognition. INTERSPEECH (2020)
Xinchi Qiu, Titouan Parcollet, Mirco Ravanelli, Nicholas D. Lane, Mohamed Morchid
Quaternion Neural Networks for Multi-Channel Distant Speech Recognition. INTERSPEECH (2020)
Daniel J. Beutel, Taner Topal, Akhil Mathur, Xinchi Qiu, Titouan Parcollet, Nicholas D. Lane
Flower: A Friendly Federated Learning Research Framework. CoRR (2020)
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 (2020)
Xinchi Qiu, Titouan Parcollet, Mirco Ravanelli, Nicholas D. Lane, Mohamed Morchid
Quaternion Neural Networks for Multi-channel Distant Speech Recognition. CoRR (2020)