1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2026
On solving symmetric multi-type orthogonal non-negative matrix tri-factorization problem
Rok Hribar, Gregor Papa, Janez Povh +1
We study the symmetric multi-type orthogonal non-negative matrix tri-factorization problem, where several symmetric non-negative matrices are simultaneously approximated by factors…
cs.LG2023★ 1 cited
Dealing with zero-inflated data: achieving SOTA with a two-fold machine learning approach
Jože M. Rožanec, Gašper Petelin, João Costa +5
In many cases, a machine learning model must learn to correctly predict a few data points with particular values of interest in a broader range of data where many target values are…