book chapter · Frontiers in artificial intelligence and applications · 2024

LightFF: Lightweight Inference for Forward-Forward Algorithm

Amin Aminifar, Baichuan Huang, Azra Abtahi, Amir Aminifar

Cited by 5Open access

Abstract

The human brain performs tasks with an outstanding energy efficiency, i.e., with approximately 20 Watts. The state-of-the-art Artificial/Deep Neural Networks (ANN/DNN), on the other hand, have recently been shown to consume massive amounts of energy. The training of these ANNs/DNNs is done almost exclusively based on the back-propagation algorithm, which is known to be biologically implausible. This has led to a new generation of forward-only techniques, including the Forward-Forward algorithm. In this paper, we propose a lightweight inference scheme specifically designed for DNNs trained using the Forward-Forward algorithm. We have evaluated our proposed lightweight inference scheme in the case of the MNIST and CIFAR datasets, as well as two real-world applications, namely, epileptic seizure detection and cardiac arrhythmia classification using wearable technologies, where complexity overheads/energy consumption is a major constraint, and demonstrate its relevance. Our code is available at https://github.com/AminAminifar/LightFF.

Cite this paper

APA 7

Aminifar, A., Huang, B., Abtahi, A., & Aminifar, A. (2024). LightFF: Lightweight Inference for Forward-Forward Algorithm. Frontiers in artificial intelligence and applications. https://doi.org/10.3233/faia240682

MLA 9

Aminifar, Amin, et al. “LightFF: Lightweight Inference for Forward-Forward Algorithm.” Frontiers in artificial intelligence and applications, 2024, https://doi.org/10.3233/faia240682.

Chicago

Aminifar, Amin, Baichuan Huang, Azra Abtahi, and Amir Aminifar. 2024. “LightFF: Lightweight Inference for Forward-Forward Algorithm.” Frontiers in artificial intelligence and applications. https://doi.org/10.3233/faia240682.

Harvard

Aminifar, A. et al. (2024) ‘LightFF: Lightweight Inference for Forward-Forward Algorithm’, Frontiers in artificial intelligence and applications. Available at: https://doi.org/10.3233/faia240682.

BibTeX

@incollection{aminifar2024lightff,
  title = {{LightFF: Lightweight Inference for Forward-Forward Algorithm}},
  author = {Aminifar, Amin and Huang, Baichuan and Abtahi, Azra and Aminifar, Amir},
  booktitle = {Frontiers in artificial intelligence and applications},
  year = {2024},
  doi = {10.3233/faia240682}
}

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