3 citations · 3 across the 1 of their papers we have counts for
2 papers
cs.DS2022★ 3 cited
-Generalized Probit Regression and Scalable Maximum Likelihood Estimation via Sketching and Coresets
Alexander Munteanu, Simon Omlor, Christian Peters
We study the -generalized probit regression model, which is a generalized linear model for binary responses. It extends the standard probit model by replacing its link function,…
cs.LG2018
Binary Input Layer: Training of CNN models with binary input data
Robert Dürichen, Thomas Rocznik, Oliver Renz +1
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…