Optical random projections for large scale machine learning

Sylvain Gigan

doi:10.1117/12.3016686

18 June 2024 Optical random projections for large scale machine learning

Sylvain Gigan

Proceedings Volume PC13017, Machine Learning in Photonics; PC130170M (2024) https://doi.org/10.1117/12.3016686
Event: SPIE Photonics Europe, 2024, Strasbourg, France

Abstract

Light propagation in disordered media can be seen as a linear operation on fields : a multiplication by a random matrix, between a set of input modes (for instance pixels of an SLM) and output modes (for instance pixels of a camera). This operation, akin to a single-layer of a neural network, can be leveraged for a wealth of signal processing and machine learning tasks. I will present some of our works, ranging from classification to time-series prediction, and importantly present our recent approaches to go beyond linear random projections, in order to provide deeper equivalent neural networks and better machine-learning performances across a variety of tasks.

Conference Presentation

Citation Download Citation

Sylvain Gigan "Optical random projections for large scale machine learning", Proc. SPIE PC13017, Machine Learning in Photonics, PC130170M (18 June 2024); https://doi.org/10.1117/12.3016686

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