1 citations · 1 across the 2 of their papers we have counts for
5 papers
Semi-supervised Nonnegative Matrix Factorization for Document Classification
Jamie Haddock, Lara Kassab, Sixian Li +9
We propose new semi-supervised nonnegative matrix factorization (SSNMF) models for document classification and provide motivation for these models as maximum likelihood estimators.…
Semi-supervised NMF Models for Topic Modeling in Learning Tasks
Jamie Haddock, Lara Kassab, Sixian Li +9
We propose several new models for semi-supervised nonnegative matrix factorization (SSNMF) and provide motivation for SSNMF models as maximum likelihood estimators given specific d…
COVID-19 Literature Topic-Based Search via Hierarchical NMF
Rachel Grotheer, Yihuan Huang, Pengyu Li +7
A dataset of COVID-19-related scientific literature is compiled, combining the articles from several online libraries and selecting those with open access and full text available.…
On Large-Scale Dynamic Topic Modeling with Nonnegative CP Tensor Decomposition
Miju Ahn, Nicole Eikmeier, Jamie Haddock +7
There is currently an unprecedented demand for large-scale temporal data analysis due to the explosive growth of data. Dynamic topic modeling has been widely used in social and dat…
benchNGS : An approach to benchmark short reads alignment tools
Farzana Rahman, Mehedi Hassan, Alona Kryshchenko +3
In the last decade a number of algorithms and associated software have been developed to align next generation sequencing (NGS) reads with relevant reference genomes. The accuracy…