Daniel J. Beutel

According to our database, Daniel J. Beutel authored at least 15 papers between 2020 and 2024.

Collaborative distances:

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

2024

Supercharging Federated Learning with Flower and NVIDIA FLARE.

Holger R. Roth, Daniel J. Beutel, Yan Cheng, Javier Fernández-Marqués, Heng Pan, Chester Chen, Zhihong Zhang, Yuhong Wen, Sean Yang, Isaac Yang, Yuan-Ting Hsieh, Ziyue Xu, Daguang Xu, Nicholas D. Lane, Andrew Feng

CoRR, 2024

Keynote Speech 4 Federated Learning for IoT.

Daniel J. Beutel

Proceedings of the 11th International Conference on Internet of Things: Systems, 2024

Federated Learning for IoT.

Daniel J. Beutel

Proceedings of the 2024 9th International Conference on Fog and Mobile Edge Computing (FMEC), 2024

2023

Federated benchmarking of medical artificial intelligence with MedPerf.

Alexandros Karargyris, Renato Umeton, Micah J. Sheller, Alejandro Aristizabal, Johnu George, Anna Wuest, Sarthak Pati, Hasan Kassem, Maximilian Zenk, Ujjwal Baid, Prakash Narayana Moorthy, Alexander Chowdhury, Junyi Guo, Sahil S. Nalawade, Jacob Rosenthal, David Kanter, Maria Xenochristou, Daniel J. Beutel, Verena Chung, Timothy Bergquist, James A. Eddy, Abubakar Abid, Lewis Tunstall, Omar Sanseviero, Dimitrios Dimitriadis, Yiming Qian, Xinxing Xu, Yong Liu, Rick Siow Mong Goh, Srini Bala, Victor Bittorf, Sreekar Reddy Puchala, Biagio Ricciuti, Soujanya Samineni, Eshna Sengupta, Akshay Chaudhari, Cody Coleman, Bala Desinghu, Gregory F. Diamos, Debo Dutta, Diane Feddema, Grigori Fursin, Xinyuan Huang, Satyananda Kashyap, Nicholas D. Lane, Indranil Mallick, Pietro Mascagni, Virendra Mehta, Cassiano Ferro Moraes, Vivek Natarajan, Nikola Nikolov, Nicolas Padoy, Gennady Pekhimenko, Vijay Janapa Reddi, G. Anthony Reina, Pablo Ribalta, Abhishek Singh, Jayaraman J. Thiagarajan, Jacob Albrecht, Thomas Wolf, Geralyn Miller, Huazhu Fu, Prashant Shah, Daguang Xu, Poonam Yadav, David Talby, Mark M. Awad, Jeremy P. Howard, Michael Rosenthal, Luigi Marchionni, Massimo Loda, Jason M. Johnson, Spyridon Bakas, Peter Mattson

Nat. Mac. Intell., July, 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

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

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

CoRR, 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

End-to-End Speech Recognition from Federated Acoustic Models.

Yan Gao, Titouan Parcollet, Salah Zaiem, Javier Fernández-Marqués, Pedro P. B. de Gusmao, Daniel J. Beutel, Nicholas D. Lane

Proceedings of the IEEE International Conference on Acoustics, 2022

2021

MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation.

Alexandros Karargyris, Renato Umeton, Micah J. Sheller, Alejandro Aristizabal, Johnu George, Srini Bala, Daniel J. Beutel, Victor Bittorf, Akshay Chaudhari, Alexander Chowdhury, Cody Coleman, Bala Desinghu, Gregory F. Diamos, Debo Dutta, Diane Feddema, Grigori Fursin, Junyi Guo, Xinyuan Huang, David Kanter, Satyananda Kashyap, Nicholas D. Lane, Indranil Mallick, Pietro Mascagni, Virendra Mehta, Vivek Natarajan, Nikola Nikolov, Nicolas Padoy, Gennady Pekhimenko, Vijay Janapa Reddi, G. Anthony Reina, Pablo Ribalta, Jacob Rosenthal, Abhishek Singh, Jayaraman J. Thiagarajan, Anna Wuest, Maria Xenochristou, Daguang Xu, Poonam Yadav, Michael Rosenthal, Massimo Loda, Jason M. Johnson, Peter Mattson

CoRR, 2021

End-to-End Speech Recognition from Federated Acoustic Models.

Yan Gao, Titouan Parcollet, Javier Fernández-Marqués, Pedro P. B. de Gusmao, Daniel J. Beutel, Nicholas D. Lane

CoRR, 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

Secure aggregation for federated learning in flower.

Kwing Hei Li, Pedro Porto Buarque de Gusmão, Daniel J. Beutel, Nicholas D. Lane

Proceedings of the DistributedML '21: Proceedings of the 2nd ACM International Workshop on Distributed Machine Learning, 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