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Rachel Grotheer
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2020 – today
- 2023
- [c6]Rachel Grotheer, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Stochastic Natural Thresholding Algorithms. ACSSC 2023: 832-836 - [i10]Rachel Grotheer, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Stochastic Natural Thresholding Algorithms. CoRR abs/2306.04730 (2023) - 2022
- [i9]Jamie Haddock, Lara Kassab, Sixian Li, Alona Kryshchenko, Rachel Grotheer, Elena Sizikova, Chuntian Wang, Thomas Merkh, R. W. M. A. Madushani, Miju Ahn, Deanna Needell, Kathryn Leonard:
Semi-supervised Nonnegative Matrix Factorization for Document Classification. CoRR abs/2203.03551 (2022) - [i8]Elena Sizikova, Joshua Vendrow, Xu Cao, Rachel Grotheer, Jamie Haddock, Lara Kassab, Alona Kryshchenko, Thomas Merkh, R. W. M. A. Madushani, Kenny Moise, Annie Ulichney, Huy V. Vo, Chuntian Wang, Megan Coffee, Kathryn Leonard, Deanna Needell:
Automatic Infectious Disease Classification Analysis with Concept Discovery. CoRR abs/2209.02415 (2022) - 2021
- [c5]Jamie Haddock, Lara Kassab, Sixian Li, Alona Kryshchenko, Rachel Grotheer, Elena Sizikova, Chuntian Wang, Thomas Merkh, R. W. M. A. Madushani, Miju Ahn, Deanna Needell, Kathryn Leonard:
Semi-supervised Nonnegative Matrix Factorization for Document Classification. ACSCC 2021: 1355-1360 - 2020
- [c4]Rachel Grotheer, Longxiu Huang, Yihuan Huang, Alona Kryshchenko, Oleksandr Kryshchenko, Pengyu Li, Xia Li, Elizaveta Rebrova, Kyung Ha, Deanna Needell:
COVID-19 Literature Topic-Based Search via Hierarchical NMF. NLP4COVID@EMNLP 2020 - [c3]Rachel Grotheer, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Stochastic Iterative Hard Thresholding for Low-Tucker-Rank Tensor Recovery. ITA 2020: 1-5 - [i7]Rachel Grotheer, Yihuan Huang, Pengyu Li, Elizaveta Rebrova, Deanna Needell, Longxiu Huang, Alona Kryshchenko, Xia Li, Kyung Ha, Oleksandr Kryshchenko:
COVID-19 Literature Topic-Based Search via Hierarchical NMF. CoRR abs/2009.09074 (2020) - [i6]Jamie Haddock, Lara Kassab, Sixian Li, Alona Kryshchenko, Rachel Grotheer, Elena Sizikova, Chuntian Wang, Thomas Merkh, R. W. M. A. Madushani, Miju Ahn, Deanna Needell, Kathryn Leonard:
Semi-supervised NMF Models for Topic Modeling in Learning Tasks. CoRR abs/2010.07956 (2020)
2010 – 2019
- 2019
- [c2]Natalie Durgin, Rachel Grotheer, Chenxi Huang, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Jointly Sparse Signal Recovery with Prior Info. ACSSC 2019: 645-649 - [c1]Natalie Durgin, Rachel Grotheer, Chenxi Huang, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Fast Hyperspectral Diffuse Optical Imaging Method with Joint Sparsity. EMBC 2019: 4758-4761 - [i5]Rachel Grotheer, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Iterative Hard Thresholding for Low CP-rank Tensor Models. CoRR abs/1908.08479 (2019) - [i4]Rachel Grotheer, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Stochastic Iterative Hard Thresholding for Low-Tucker-Rank Tensor Recovery. CoRR abs/1909.10132 (2019) - 2018
- [i3]Natalie Durgin, Rachel Grotheer, Chenxi Huang, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Compressed Anomaly Detection with Multiple Mixed Observations. CoRR abs/1801.10264 (2018) - 2017
- [i2]Jing Qin, Shuang Li, Deanna Needell, Anna Ma, Rachel Grotheer, Chenxi Huang, Natalie Durgin:
Stochastic Greedy Algorithms For Multiple Measurement Vectors. CoRR abs/1711.01521 (2017) - [i1]Natalie Durgin, Rachel Grotheer, Chenxi Huang, Shuang Li, Anna Ma, Deanna Needell, Jing Qin:
Sparse Randomized Kaczmarz for Support Recovery of Jointly Sparse Corrupted Multiple Measurement Vectors. CoRR abs/1711.02743 (2017)
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