Seuraa
Cencheng Shen
Cencheng Shen
Vahvistettu sähköpostiosoite verkkotunnuksessa udel.edu
Nimike
Viittaukset
Viittaukset
Vuosi
From distance correlation to multiscale graph correlation
C Shen, CE Priebe, JT Vogelstein
Journal of the American Statistical Association, 1-22, 2019
702019
Sparse projection oblique randomer forests
TM Tomita, J Browne, C Shen, J Chung, JL Patsolic, B Falk, CE Priebe, ...
Journal of machine learning research 21 (104), 1-39, 2020
46*2020
The chi-square test of distance correlation
C Shen, S Panda, JT Vogelstein
Journal of Computational and Graphical Statistics 31 (1), 254-262, 2022
442022
The exact equivalence of distance and kernel methods in hypothesis testing
C Shen, JT Vogelstein
AStA Advances in Statistical Analysis 105, 385-403, 2021
422021
Generalized canonical correlation analysis for classification
C Shen, M Sun, M Tang, CE Priebe
Journal of Multivariate Analysis 130, 310-322, 2014
412014
Discovering and deciphering relationships across disparate data modalities
JT Vogelstein, EW Bridgeford, Q Wang, CE Priebe, M Maggioni, C Shen
Elife 8, e41690, 2019
39*2019
Network dependence testing via diffusion maps and distance-based correlations
Y Lee, C Shen, CE Priebe, JT Vogelstein
Biometrika 106 (4), 857-873, 2019
252019
Robust vertex classification
L Chen, C Shen, JT Vogelstein, CE Priebe
IEEE transactions on pattern analysis and machine intelligence 38 (3), 578-590, 2015
202015
hyppo: A multivariate hypothesis testing Python package
S Panda, S Palaniappan, J Xiong, EW Bridgeford, R Mehta, C Shen, ...
arXiv preprint arXiv:1907.02088, 2019
19*2019
Manifold matching using shortest-path distance and joint neighborhood selection
C Shen, JT Vogelstein, CE Priebe
Pattern Recognition Letters 92, 41-48, 2017
172017
Sparse representation classification beyond ℓ1 minimization and the subspace assumption
C Shen, L Chen, Y Dong, CE Priebe
IEEE Transactions on Information Theory 66 (8), 5061-5071, 2020
162020
Nonpar manova via independence testing
S Panda, C Shen, R Perry, J Zorn, A Lutz, CE Priebe, JT Vogelstein
arXiv e-prints, arXiv: 1910.08883, 2019
16*2019
Discovering the Signal Subgraph: An Iterative Screening Approach on Graphs
C Shen, S Wang, A Badea, CE Priebe, JT Vogelstein
arXiv e-prints, arXiv: 1801.07683, 2018
14*2018
Estimating information-theoretic quantities with uncertainty forests
R Guo, R Mehta, J Arroyo, H Helm, C Shen, JT Vogelstein
arXiv, arXiv: 1907.00325, 2019
10*2019
One-Hot Graph Encoder Embedding
C Shen, Q Wang, CE Priebe
IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (6), 7933 …, 2023
82023
Independence testing for temporal data
C Shen, J Chung, R Mehta, T Xu, JT Vogelstein
arXiv e-prints, arXiv: 1908.06486, 2019
7*2019
On the incommensurability phenomenon
DE Fishkind, C Shen, Y Park, CE Priebe
Journal of Classification 33, 185-209, 2016
62016
Graph independence testing
J Xiong, C Shen, J Arroyo, JT Vogelstein
arXiv preprint arXiv:1906.03661, 2019
52019
A simple spectral failure mode for graph convolutional networks
CE Priebe, C Shen, N Huang, T Chen
IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (11), 8689 …, 2021
42021
Decision forests induce characteristic kernels
C Shen, JT Vogelstein
arXiv preprint arXiv:1812.00029, 2018
42018
Järjestelmä ei voi suorittaa toimenpidettä nyt. Yritä myöhemmin uudelleen.
Artikkelit 1–20