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The Manifold Scattering Transform for High-Dimensional Point Cloud Data



Joyce Chew , Holly R. Steach , Siddharth Viswanath , Hau-Tieng Wu , Matthew Hirn , Deanna Needell , Smita Krishnaswamy , Michael Perlmutter

* Accepted for publication in the TAG in DS Workshop at ICML 

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Distributed randomized Kaczmarz for the adversarial workers



Xia Li , Longxiu Huang , Deanna Needell


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Semi-supervised Nonnegative Matrix Factorization for Document Classification



Jamie Haddock , Lara Kassab , Sixian Li , Alona Kryshchenko , Rachel Grotheer , Elena Sizikova , Chuntian Wang , Thomas Merkh , RWMA Madushani , Miju Ahn , Deanna Needell , Kathryn Leonard

* arXiv admin note: substantial text overlap with arXiv:2010.07956 

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Guided Semi-Supervised Non-negative Matrix Factorization on Legal Documents



Pengyu Li , Christine Tseng , Yaxuan Zheng , Joyce A. Chew , Longxiu Huang , Benjamin Jarman , Deanna Needell

* 14 pages, 4 figures 

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On audio enhancement via online non-negative matrix factorization



Andrew Sack , Wenzhao Jiang , Michael Perlmutter , Palina Salanevich , Deanna Needell


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A Generalized Hierarchical Nonnegative Tensor Decomposition



Joshua Vendrow , Jamie Haddock , Deanna Needell

* 6 pages, 2 figues, 3 tables 

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Fast Robust Tensor Principal Component Analysis via Fiber CUR Decomposition



HanQin Cai , Zehan Chao , Longxiu Huang , Deanna Needell

* Accepted to Workshop on Robust Subspace Learning and Applications in Computer Vision, International Conference on Computer Vision (ICCV) 2021 

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Analysis of Legal Documents via Non-negative Matrix Factorization Methods



Ryan Budahazy , Lu Cheng , Yihuan Huang , Andrew Johnson , Pengyu Li , Joshua Vendrow , Zhoutong Wu , Denali Molitor , Elizaveta Rebrova , Deanna Needell

* 16 pages, 4 figures 

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Mode-wise Tensor Decompositions: Multi-dimensional Generalizations of CUR Decompositions



HanQin Cai , Keaton Hamm , Longxiu Huang , Deanna Needell


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Robust CUR Decomposition: Theory and Imaging Applications



HanQin Cai , Keaton Hamm , Longxiu Huang , Deanna Needell


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