1 citations · 2 across the 6 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…
On a Guided Nonnegative Matrix Factorization
Joshua Vendrow, Jamie Haddock, Elizaveta Rebrova +1
Fully unsupervised topic models have found fantastic success in document clustering and classification. However, these models often suffer from the tendency to learn less-than-mean…
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…
Data-driven Algorithm Selection and Parameter Tuning: Two Case studies in Optimization and Signal Processing
Jesus A. De Loera, Jamie Haddock, Anna Ma +1
Machine learning algorithms typically rely on optimization subroutines and are well-known to provide very effective outcomes for many types of problems. Here, we flip the reliance…