TinyML Techniques for running Machine Learning models on Edge Devices

Author:

Mukherjee Arijit1ORCID,Ukil Arijit1ORCID,Dey Swarnava1ORCID,Kulkarni Gitesh1ORCID

Affiliation:

1. Embedded Devices & Intelligent Systems, TCS Research, IN

Publisher

ACM

Reference23 articles.

1. Bowen Baker Otkrist Gupta Nikhil Naik and Ramesh Raskar. 2016. Designing Neural Network Architectures using Reinforcement Learning. (2016). Bowen Baker Otkrist Gupta Nikhil Naik and Ramesh Raskar. 2016. Designing Neural Network Architectures using Reinforcement Learning. (2016).

2. Han Cai Tianyao Chen Weinan Zhang Yong Yu and Jun Wang. 2017. Efficient Architecture Search by Network Transformation. CoRR abs/1707.04873(2017). Han Cai Tianyao Chen Weinan Zhang Yong Yu and Jun Wang. 2017. Efficient Architecture Search by Network Transformation. CoRR abs/1707.04873(2017).

3. Update Compression for Deep Neural Networks on the Edge

4. Model Compression and Acceleration for Deep Neural Networks: The Principles, Progress, and Challenges

5. Robert David , Jared Duke , Advait Jain , Vijay Janapa Reddi , Nat Jeffries , Jian Li , Nick Kreeger , Ian Nappier , Meghna Natraj , Tiezhen Wang , Pete Warden , and Rocky Rhodes . 2021 . TensorFlow Lite Micro: Embedded Machine Learning for TinyML Systems . In Proceedings of Machine Learning and Systems, A. Smola, A. Dimakis, and I. Stoica (Eds.). Vol. 3. 800–811 . https://proceedings.mlsys.org/paper/2021/file/d2ddea18f00665ce8623e36bd4e3c7c5-Paper.pdf Robert David, Jared Duke, Advait Jain, Vijay Janapa Reddi, Nat Jeffries, Jian Li, Nick Kreeger, Ian Nappier, Meghna Natraj, Tiezhen Wang, Pete Warden, and Rocky Rhodes. 2021. TensorFlow Lite Micro: Embedded Machine Learning for TinyML Systems. In Proceedings of Machine Learning and Systems, A. Smola, A. Dimakis, and I. Stoica (Eds.). Vol. 3. 800–811. https://proceedings.mlsys.org/paper/2021/file/d2ddea18f00665ce8623e36bd4e3c7c5-Paper.pdf

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