2 citations · 3 across the 2 of their papers we have counts for
3 papers
q-bio.GN2022★ 1 cited
NLP-based classification of software tools for metagenomics sequencing data analysis into EDAM semantic annotation
Kaoutar Daoud Hiri, Matjaž Hren, Tomaž Curk
Motivation: The rapid growth of metagenomics sequencing data makes metagenomics increasingly dependent on computational and statistical methods for fast and efficient analysis. Con…
cs.LG2022★ 2 cited
FastSTMF: Efficient tropical matrix factorization algorithm for sparse data
Amra Omanović, Polona Oblak, Tomaž Curk
Matrix factorization, one of the most popular methods in machine learning, has recently benefited from introducing non-linearity in prediction tasks using tropical semiring. The no…
cs.LG2016
Learning the kernel matrix via predictive low-rank approximations
Martin Stražar, Tomaž Curk
Efficient and accurate low-rank approximations of multiple data sources are essential in the era of big data. The scaling of kernel-based learning algorithms to large datasets is l…