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17 March 2023 Optimization and training of the nonlinear Schrödinger kernel
Tingyi Zhou, Bahram Jalali
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Proceedings Volume PC12438, AI and Optical Data Sciences IV; PC1243809 (2023) https://doi.org/10.1117/12.2651361
Event: SPIE OPTO, 2023, San Francisco, California, United States
Abstract
Nonlinear Schrödinger Kernel is a new concept in computing using an optical system known as Nonlinear Schrödinger Kernel to perform machine learning acceleration. It connects information theory to nonlinear optical spectrum engineering, showing that this approach can effectively relieve the computational burden on the digital computer by elevating inference speed while reducing data dimension. A data encoding scheme is adopted to optimize the performance of the Nonlinear Schrödinger Kernel.
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Tingyi Zhou and Bahram Jalali "Optimization and training of the nonlinear Schrödinger kernel", Proc. SPIE PC12438, AI and Optical Data Sciences IV, PC1243809 (17 March 2023); https://doi.org/10.1117/12.2651361
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KEYWORDS
Ultrafast phenomena
Aerospace engineering
Artificial intelligence
Classification systems
Complex systems
Dimension reduction
Genetic algorithms
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