Re-thinking Efficiency in Deep Learning under Accelerators and commodity and processors

Project Information

REDIAL

Grant agreement ID: 805194

DOI

10.3030/805194

Project closed

EC signature date 10 October 2019

Start date 1 September 2020

End date 31 August 2025

Funded under

• EXCELLENT SCIENCE - European Research Council (ERC)

Total cost

€ 1 495 036,00

EU contribution

€ 1 495 036,00

Coordinated by

THE CHANCELLOR MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE
United Kingdom

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Publications

Conference proceedings (15)

Secure aggregation for federated learning in flower

Author(s): Kwing Hei Li; Pedro Porto Buarque de Gusmão; Daniel J. Beutel; Nicholas D. Lane
Published in: Proceedings of the 2nd ACM International Workshop on Distributed Machine Learning, Issue 1, 2021, Page(s) 8-14
Publisher: ACM
DOI: 10.48550/arxiv.2205.06117

PROSPECT PRUNING: FINDING TRAINABLE WEIGHTSAT INITIALIZATION USING META-GRADIENTS

Author(s): Milad Alizadeh, Shyam A. Tailor, Luisa Zintgraf 3 Joost van Amersfoort 1 Sebastian Farquhar 1 Nicholas Donald Lane 2,4 Yarin Gal 1
Published in: International Conference on Learning Representations, Issue 1, 2022
Publisher: ICLR

Differentiable Neural Network Pruning to Enable Smart Applications on Microcontrollers

Author(s): Edgar Liberis, Nicholas D Lane
Published in: 2023, ISSN 2474-9567
Publisher: ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies IMWUT
DOI: 10.48550/arxiv.2110.08350

Federated Self-supervised Speech Representations: Are We There Yet?

Author(s): Yan Gao, Javier Fernandez-Marques, Titouan Parcollet, Abhinav Mehrotra, Nicholas D. Lane
Published in: 2022
Publisher: Interspeech 2022

Di!erentiable Neural Network Pruning to Enable Smart Applicationson Microcontrollers

Author(s): EDGAR LIBERIS, NICHOLAS D. LANE
Published in: ACM IMWUT Journal, Issue 1, 2022
Publisher: ACM

Deep learning on microcontrollers

Author(s): Svoboda, Filip; Fernandez-Marques, Javier; Liberis, Edgar; Lane, Nicholas D.
Published in: isbn: 9781450392549, Issue 1, 2022
Publisher: 2nd Workshop on Machine Learning and Systems, EuroMLSys

Gradient-less Federated Gradient Boosting Tree with Learnable Learning Rates

Author(s): Chenyang Ma, Xinchi Qiu, Daniel Beutel, Nicholas Lane
Published in: 2023
Publisher: 3rd Workshop on Machine Learning and Systems

Federated Self-supervised Learning for Video Understanding

Author(s): Yasar Abbas Ur Rehman, Yan Gao, Jiajun Shen, Pedro Porto Buarque de Gusmão, Nicholas Lane
Published in: 2022
Publisher: 17th European Conference on Computer Vision

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

Author(s): Qiu, Xinchi; Fernandez-Marques, Javier; Gusmao, Pedro PB; Gao, Yan; Parcollet, Titouan; Lane, Nicholas Donald
Published in: 2022
Publisher: International Conference on Learning Representations
DOI: 10.48550/arxiv.2208.02507

End-to-End Speech Recognition from Federated Acoustic Models

Author(s): Yan Gao, Titouan Parcollet, Salah Zaiem, Javier Fernandez-Marques, Pedro P. B. de Gusmao, Daniel J. Beutel, Nicholas Lane
Published in: 2022
Publisher: IEEE International Conference on Acoustics, Speech and Signal Processing

μNAS: Constrained Neural Architecture Search for Microcontrollers

Author(s): Edgar Liberis, Łukasz Dudziak, Nicholas D. Lane
Published in: Proceedings of the 1st Workshop on Machine Learning and Systems (EuroMLSys), 2021
Publisher: ACM

Can Fair Federated Learning reduce the need for Personalisation?

Author(s): Alex Iacob, Pedro Porto Buarque Gusmão, Nicholas Lane
Published in: 2023
Publisher: 3rd Workshop on Machine Learning and Systems

Protea: Client profiling within federated systems using flower

Author(s): Wanru Zhao, Xinchi Qiu, Javier Fernandez-Marques, Pedro PB de Gusmão, Nicholas D Lane
Published in: 2022
Publisher: 1st ACM Workshop on Data Privacy and Federated Learning Technologies for Mobile Edge Network

Deep Learning on Microcontrollers: A Studyon Deployment Costs and Challenges

Author(s): Filip Svoboda Javier Fernandez-Marques Edgar Liberis Nicholas D. Lane
Published in: Proceedings of EuroMLSys, 2022
Publisher: ACM
DOI: 10.1145/3517207.3526978

FedVal: Different good or different bad in federated learning

Author(s): Viktor Valadi, Xinchi Qiu, Pedro Porto Buarque de Gusmão, Nicholas D. Lane, Mina Alibeigi
Published in: 2023
Publisher: 32nd USENIX Security Symposium

Peer reviewed articles (2)

MobiVQA: Efficient On-Device Visual Question Answering

Author(s): Qingqing Cao, Prerna Khanna, Nicholas D. Lane, Aruna Balasubramanian
Published in: ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Issue 1, 2022, Page(s) Volume 6 Issue 2. July 2022, ISSN 2474-9567
Publisher: ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies IMWUT

A first look into the carbon footprint of federated learning

Author(s): Xinchi Qiu, Titouan Parcollet, Javier Fernandez-Marques, Pedro PB de Gusmao, Yan Gao, Daniel J Beutel, Taner Topal, Akhil Mathur, Nicholas D Lane
Published in: Journal of Machine Learning Research, 2023, Page(s) Volume 24 Issue 1. January 2023, ISSN 1533-7928
Publisher: Journal of Machine Learning Research

Other (1)

Pex: Memory-efficient Microcontroller Deep Learning through Partial Execution

Author(s): Edgar Liberis, Nicholas D. Lane
Published in: 2022
Publisher: ArXiv pre-print