Xinchi Qiu

According to our database, Xinchi Qiu authored at least 18 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

FedAnchor: Enhancing Federated Semi-Supervised Learning with Label Contrastive Loss for Unlabeled Clients.

Xinchi Qiu, Yan Gao, Lorenzo Sani, Heng Pan, Wanru Zhao, Pedro P. B. de Gusmao, Mina Alibeigi, Alex Iacob, Nicholas D. Lane

CoRR, 2024

2023

A First Look into the Carbon Footprint of Federated Learning.

Xinchi Qiu, Titouan Parcollet, Javier Fernández-Marqués, Pedro P. B. de Gusmao, Yan Gao, Daniel J. Beutel, Taner Topal, Akhil Mathur, Nicholas D. Lane

J. Mach. Learn. Res., 2023

High-throughput Simulation of Federated Learning via Resource-Aware Client Placement.

Lorenzo Sani, Pedro Porto Buarque de Gusmão, Alex Iacob, Wanru Zhao, Xinchi Qiu, Yan Gao, Javier Fernández-Marquás, Nicholas Donald Lane

CoRR, 2023

vFedSec: Efficient Secure Aggregation for Vertical Federated Learning via Secure Layer.

Xinchi Qiu, Heng Pan, Wanru Zhao, Chenyang Ma, Pedro P. B. de Gusmao, Nicholas D. Lane

CoRR, 2023

EXACT: Extensive Attack for Split Learning.

Xinchi Qiu, Ilias Leontiadis, Luca Melis, Alexandre Sablayrolles, Pierre Stock

CoRR, 2023

Efficient Vertical Federated Learning with Secure Aggregation.

Xinchi Qiu, Heng Pan, Wanru Zhao, Chenyang Ma, Pedro Porto Buarque de Gusmão, Nicholas D. Lane

CoRR, 2023

Gradient-less Federated Gradient Boosting Trees with Learnable Learning Rates.

Chenyang Ma, Xinchi Qiu, Daniel J. Beutel, Nicholas D. Lane

CoRR, 2023

FedVal: Different good or different bad in federated learning.

Viktor Valadi, Xinchi Qiu, Pedro Porto Buarque de Gusmão, Nicholas D. Lane, Mina Alibeigi

Proceedings of the 32nd USENIX Security Symposium, 2023

FedL2P: Federated Learning to Personalize.

Royson Lee, Minyoung Kim, Da Li, Xinchi Qiu, Timothy M. Hospedales, Ferenc Huszar, Nicholas D. Lane

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Gradient-less Federated Gradient Boosting Tree with Learnable Learning Rates.

Chenyang Ma, Xinchi Qiu, Daniel J. Beutel, Nicholas D. Lane

Proceedings of the 3rd Workshop on Machine Learning and Systems, 2023

2022

ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity.

Xinchi Qiu, Javier Fernández-Marqués, Pedro P. B. de Gusmao, Yan Gao, Titouan Parcollet, Nicholas Donald Lane

Proceedings of the Tenth International Conference on Learning Representations, 2022

Protea: client profiling within federated systems using flower.

Wanru Zhao, Xinchi Qiu, Javier Fernández-Marqués, Pedro P. B. de Gusmao, Nicholas D. Lane

Proceedings of the 1st ACM Workshop on Data Privacy and Federated Learning Technologies for Mobile Edge Network, 2022

2021

On-device Federated Learning with Flower.

Akhil Mathur, Daniel J. Beutel, Pedro Porto Buarque de Gusmão, Javier Fernández-Marqués, Taner Topal, Xinchi Qiu, Titouan Parcollet, Yan Gao, Nicholas D. Lane

CoRR, 2021

A first look into the carbon footprint of federated learning.

Xinchi Qiu, Titouan Parcollet, Javier Fernández-Marqués, Pedro Porto Buarque de Gusmão, Daniel J. Beutel, Taner Topal, Akhil Mathur, Nicholas D. Lane

CoRR, 2021

2020

A first look into the carbon footprint of federated learning.

Xinchi Qiu, Titouan Parcollet, Daniel J. Beutel, Taner Topal, Akhil Mathur, Nicholas D. Lane

CoRR, 2020

Flower: A Friendly Federated Learning Research Framework.

Daniel J. Beutel, Taner Topal, Akhil Mathur, Xinchi Qiu, Titouan Parcollet, Nicholas D. Lane

CoRR, 2020

Quaternion Neural Networks for Multi-Channel Distant Speech Recognition.

Xinchi Qiu, Titouan Parcollet, Mirco Ravanelli, Nicholas D. Lane, Mohamed Morchid

Proceedings of the Interspeech 2020, 2020

FusionRNN: Shared Neural Parameters for Multi-Channel Distant Speech Recognition.

Titouan Parcollet, Xinchi Qiu, Nicholas D. Lane

Proceedings of the Interspeech 2020, 2020