David Hong

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 22

Top Topics

Tensor Decomposition

Robust Classification

Subspace Clustering

Top Venues

SIAM J. Math. Data Sci.

IEEE Trans. Inf. Theory

Publications

Edgar Dobriban, Hamed Hassani, David Hong, Alexander Robey
Provable Tradeoffs in Adversarially Robust Classification. IEEE Trans. Inf. Theory 69 (12) (2023)
David Hong, Fan Yang, Jeffrey A. Fessler, Laura Balzano
Optimally Weighted PCA for High-Dimensional Heteroscedastic Data. SIAM J. Math. Data Sci. 5 (1) (2023)
David Hong, Kyle Gilman, Laura Balzano, Jeffrey A. Fessler
HePPCAT: Probabilistic PCA for Data With Heteroscedastic Noise. IEEE Trans. Signal Process. 69 (2021)
Edgar Dobriban, Hamed Hassani, David Hong, Alexander Robey
Provable tradeoffs in adversarially robust classification. CoRR (2020)
Shunbo Lei, David Hong, Johanna L. Mathieu, Ian A. Hiskens
Baseline Estimation of Commercial Building HVAC Fan Power Using Tensor Completion. CoRR (2020)
Tamara G. Kolda, David Hong
Stochastic Gradients for Large-Scale Tensor Decomposition. SIAM J. Math. Data Sci. 2 (4) (2020)
David Hong, Tamara G. Kolda, Jed A. Duersch
Generalized Canonical Polyadic Tensor Decomposition. SIAM Rev. 62 (1) (2020)
David Hong, Shunbo Lei, Johanna L. Mathieu, Laura Balzano
Exploration of tensor decomposition applied to commercial building baseline estimation. GlobalSIP (2019)
Tamara G. Kolda, David Hong
Stochastic Gradients for Large-Scale Tensor Decomposition. CoRR (2019)
Il Yong Chun, David Hong, Ben Adcock, Jeffrey A. Fessler
Convolutional Analysis Operator Learning: Dependence on Training Data. IEEE Signal Process. Lett. 26 (8) (2019)
Il Yong Chun, David Hong, Ben Adcock, Jeffrey A. Fessler
Convolutional Analysis Operator Learning: Dependence on Training Data. CoRR (2019)
Caroline Crockett, David Hong, Il Yong Chun, Jeffrey A. Fessler
Incorporating Handcrafted Filters in Convolutional Analysis Operator Learning for Ill-Posed Inverse Problems. CAMSAP (2019)
David Hong, Laura Balzano, Jeffrey A. Fessler
Probabilistic PCA for Heteroscedastic Data. CAMSAP (2019)
David Hong, Laura Balzano, Jeffrey A. Fessler
Asymptotic performance of PCA for high-dimensional heteroscedastic data. J. Multivar. Anal. 167 (2018)
Greg Ongie, David Hong, Dejiao Zhang, Laura Balzano
Online Estimation of Coherent Subspaces with Adaptive Sampling. SSP (2018)
David Hong, Tamara G. Kolda, Jed A. Duersch
Generalized Canonical Polyadic Tensor Decomposition. CoRR (2018)
David Hong, Robert P. Malinas, Jeffrey A. Fessler, Laura Balzano
Learning Dictionary-Based Unions of Subspaces for Image Denoising. EUSIPCO (2018)
Christof Seiler, Tamar Green, David Hong, Lindsay Chromik, Lynne Huffman, Susan P. Holmes, Allan L. Reiss
Multi-Table Differential Correlation Analysis of Neuroanatomical and Cognitive Interactions in Turner Syndrome. Neuroinformatics 16 (1) (2018)
Ashkan Yousefpour, Caleb Fung, Tam Nguyen, David Hong, Daniel Zhang
Instant Accident Reporting and Crowdsensed Road Condition Analytics for Smart Cities. CoRR (2017)
John Lipor, David Hong, Dejiao Zhang, Laura Balzano
Subspace Clustering using Ensembles of $K$-Subspaces. CoRR (2017)
Greg Ongie, David Hong, Dejiao Zhang, Laura Balzano
Enhanced online subspace estimation via adaptive sensing. ACSSC (2017)
David Hong, Laura Balzano, Jeffrey A. Fessler
Towards a theoretical analysis of PCA for heteroscedastic data. Allerton (2016)