f-divergence regularization gives comparable or better oxide-weight predictions than L1, L2, and dropout on ChemCam and SuperCam LIBS data, with further gains when combined.
The prediction of soil chemical and physical properties from mid-infrared spectroscopy and combined partial least-squares regression and neural networks (pls-nn) analysis,
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Regularization via f-Divergence: An Application to Multi-Oxide Spectroscopic Analysis
f-divergence regularization gives comparable or better oxide-weight predictions than L1, L2, and dropout on ChemCam and SuperCam LIBS data, with further gains when combined.