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David Hong
David Hong
Assistant Professor, Department of Electrical and Computer Engineering, University of Delaware
Verified email at udel.edu - Homepage
Title
Cited by
Cited by
Year
Generalized canonical polyadic tensor decomposition
D Hong, TG Kolda, JA Duersch
SIAM Review 62 (1), 133-163, 2020
1392020
Asymptotic performance of PCA for high-dimensional heteroscedastic data
D Hong, L Balzano, JA Fessler
Journal of multivariate analysis 167, 435-452, 2018
602018
Provable tradeoffs in adversarially robust classification
E Dobriban, H Hassani, D Hong, A Robey
Accepted to IEEE Transactions on Information Theory, To appear, 2022
552022
Using viral load and epidemic dynamics to optimize pooled testing in resource-constrained settings
B Cleary, JA Hay, B Blumenstiel, M Harden, M Cipicchio, J Bezney, ...
Science translational medicine 13 (589), eabf1568, 2021
552021
Stochastic gradients for large-scale tensor decomposition
TG Kolda, D Hong
SIAM Journal on Mathematics of Data Science 2 (4), 1066-1095, 2020
502020
Optimally Weighted PCA for High-Dimensional Heteroscedastic Data
D Hong, F Yang, JA Fessler, L Balzano
SIAM Journal on Mathematics of Data Science 5 (1), 222-250, 2023
33*2023
Subspace clustering using ensembles of K-subspaces
J Lipor, D Hong, YS Tan, L Balzano
Information and Inference: A Journal of the IMA 10 (1), 73-107, 2021
262021
Closed-Form Expressions for Minimizing Total Harmonic Distortion in Three-Phase Multilevel Converters
D Hong, S Bai, SM Lukic
IEEE Transactions on Power Electronics 29 (10), 5229-5241, 2014
242014
Convolutional Analysis Operator Learning: Dependence on Training Data
IY Chun, D Hong, B Adcock, JA Fessler
IEEE Signal Processing Letters 26 (8), 1137-1141, 2019
182019
Towards a theoretical analysis of PCA for heteroscedastic data
D Hong, L Balzano, JA Fessler
2016 54th Annual Allerton Conference on Communication, Control, and …, 2016
172016
Selecting the number of components in PCA via random signflips
D Hong, Y Sheng, E Dobriban
arXiv preprint arXiv:2012.02985, 2020
142020
HePPCAT: Probabilistic PCA for data with Heteroscedastic noise
D Hong, K Gilman, L Balzano, JA Fessler
IEEE Transactions on Signal Processing 69, 4819-4834, 2021
132021
Group testing via hypergraph factorization applied to COVID-19
D Hong, R Dey, X Lin, B Cleary, E Dobriban
Nature communications 13 (1), 1837, 2022
10*2022
Enhanced online subspace estimation via adaptive sensing
G Ongie, D Hong, D Zhang, L Balzano
2017 51st Asilomar Conference on Signals, Systems, and Computers, 993-997, 2017
62017
Learning Dictionary-Based Unions of Subspaces for Image Denoising
D Hong, RP Malinas, JA Fessler, L Balzano
2018 26th European Signal Processing Conference (EUSIPCO), 1597-1601, 2018
42018
Generic Properties of Koopman Eigenfunctions for Stable Fixed Points and Periodic Orbits
MD Kvalheim, D Hong, S Revzen
IFAC-PapersOnLine 54 (9), 267-272, 2021
32021
Baseline estimation of commercial building HVAC fan power using tensor completion
S Lei, D Hong, JL Mathieu, IA Hiskens
Electric Power Systems Research 189, 106624, 2020
22020
Exploiting HF Ambient Noise to Synchronize Distributed Receivers
D Hong, JL Krolik
Radio Science Meeting (USNC-URSI NRSM), 2013 US National Committee of URSI …, 2013
12013
Learning Low-Dimensional Models for Heterogeneous Data
D Hong
2019
Generalized CP Decomposition for Alternative Loss Functions.
TG Kolda, CI Anderson-Bergman, JA Duersch, D Hong
Sandia National Lab.(SNL-CA), Livermore, CA (United States), 2018
2018
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