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20162024
most citedCOVID-19 Time-series Prediction by Joint Dictionary Learning and Online NMF

3 citations · 11 across the 23 of their papers we have counts for

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Showing 2020Show all

10 papers · 1 filter

cs.LG2020

Applications of Online Nonnegative Matrix Factorization to Image and Time-Series Data

Hanbaek Lyu, Georg Menz, Deanna Needell +1

Online nonnegative matrix factorization (ONMF) is a matrix factorization technique in the online setting where data are acquired in a streaming fashion and the matrix factors are u…

cs.LG2020

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…

cs.LG2020

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…

cs.DL2020

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.…

stat.ML2020

Clustering of Nonnegative Data and an Application to Matrix Completion

C. Strohmeier, D. Needell

In this paper, we propose a simple algorithm to cluster nonnegative data lying in disjoint subspaces. We analyze its performance in relation to a certain measure of correlation bet…

cs.CY20201 cited

Feature Selection on Lyme Disease Patient Survey Data

Joshua Vendrow, Jamie Haddock, Deanna Needell +1

Lyme disease is a rapidly growing illness that remains poorly understood within the medical community. Critical questions about when and why patients respond to treatment or stay i…