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Found 2 papers, 1 papers with code
$p$-Generalized Probit Regression and Scalable Maximum Likelihood Estimation via Sketching and Coresets
We study the $p$-generalized probit regression model, which is a generalized linear model for binary responses.
Binary Input Layer: Training of CNN models with binary input data
For the efficient execution of deep convolutional neural networks (CNN) on edge devices, various approaches have been presented which reduce the bit width of the network parameters down to 1 bit.
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