11 citations · 24 across the 15 of their papers we have counts for
4 papers · 1 filter
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…
Sparseness-constrained Nonnegative Tensor Factorization for Detecting Topics at Different Time Scales
Lara Kassab, Alona Kryshchenko, Hanbaek Lyu +4
Temporal data (such as news articles or Twitter feeds) often consists of a mixture of long-lasting trends and popular but short-lasting topics of interest. A truly successful topic…
An Adaptation for Iterative Structured Matrix Completion
Henry Adams, Lara Kassab, Deanna Needell
The task of predicting missing entries of a matrix, from a subset of known entries, is known as \textit{matrix completion}. In today's data-driven world, data completion is essenti…
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…