18 citations · 43 across the 8 of their papers we have counts for
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cs.LG2019★ 9 cited
GENO -- GENeric Optimization for Classical Machine Learning
Sören Laue, Matthias Mitterreiter, Joachim Giesen
Although optimization is the longstanding algorithmic backbone of machine learning, new models still require the time-consuming implementation of new solvers. As a result, there ar…
cs.LG2019★ 4 cited
Ising Models with Latent Conditional Gaussian Variables
Frank Nussbaum, Joachim Giesen
Ising models describe the joint probability distribution of a vector of binary feature variables. Typically, not all the variables interact with each other and one is interested in…