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Cheolwoo Park
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2020 – today
- 2024
- [j16]Jinyang Chen
, Cheolwoo Park
A deep learning paradigm for medical imaging data. Expert Syst. Appl. 255: 124480 (2024) - 2023
- [j15]Minje Park, Jaeseon Kim, Sungchul Shin, Cheolwoo Park, Jong-June Jeon, Soon-Sun Kwon, Hosik Choi
Quantile estimation for encrypted data. Appl. Intell. 53(21): 24782-24791 (2023) - [j14]Il-Suk Kang, Hosik Choi, Young Joo Yoon, Junyoung Park, Soon-Sun Kwon, Cheolwoo Park
Fréchet distance-based cluster analysis for multi-dimensional functional data. Stat. Comput. 33(4): 75 (2023) - [c5]Junyoung Park, Jeongyoun Ahn, Cheolwoo Park:
Kernel Sufficient Dimension Reduction and Variable Selection for Compositional Data via Amalgamation. ICML 2023: 27034-27047 - [c4]Bonwoo Lee, Jeongyoun Ahn, Cheolwoo Park:
Minimax Risks and Optimal Procedures for Estimation under Functional Local Differential Privacy. NeurIPS 2023 - 2022
- [j13]Arunava Samaddar, Brooke S. Jackson, Christopher J. Helms, Nicole A. Lazar, Jennifer E. McDowell, Cheolwoo Park
A group comparison in fMRI data using a semiparametric model under shape invariance. Comput. Stat. Data Anal. 167: 107361 (2022) - [j12]J. C. Poythress, Jeongyoun Ahn, Cheolwoo Park
Low-rank, Orthogonally Decomposable Tensor Regression With Application to Visual Stimulus Decoding of fMRI Data. J. Comput. Graph. Stat. 31(1): 190-203 (2022) - [c3]Junyoung Park, Changwon Yoon, Cheolwoo Park, Jeongyoun Ahn:
Kernel Methods for Radial Transformed Compositional Data with Many Zeros. ICML 2022: 17458-17472 - [c2]Jinyang Chen, Cheolwoo Park, Yuan Ke:
Learning High Dimensional Multi-response Linear Models with Non-oracular Quantum Search. QCE 2022: 1-12
2010 – 2019
- 2017
- [j11]Li-Yu Wang, Cheolwoo Park
Tracking concept drift using a constrained penalized regression combiner. Comput. Stat. Data Anal. 108: 52-69 (2017) - 2015
- [j10]Yongho Jeon, Jeongyoun Ahn, Cheolwoo Park
A Nonparametric Kernel Approach to Interval-Valued Data Analysis. Technometrics 57(4): 566-575 (2015) - 2013
- [j9]Cheolwoo Park
Statistical inference and visualization in scale-space using local likelihood. Comput. Stat. Data Anal. 57(1): 336-348 (2013) - 2012
- [j8]Jeongyoun Ahn, Muliang Peng, Cheolwoo Park
A resampling approach for interval-valued data regression. Stat. Anal. Data Min. 5(4): 336-348 (2012) - 2010
- [i1]Cheolwoo Park, Félix Hernández-Campos, J. S. Marron, Kevin Jeffay, F. Donelson Smith:
Analysis of dependence among size, rate and duration in internet flows. CoRR abs/1010.1108 (2010)
2000 – 2009
- 2008
- [j7]Cheolwoo Park
SiZer analysis for the comparison of regression curves. Comput. Stat. Data Anal. 52(8): 3954-3970 (2008) - 2007
- [j6]Cheolwoo Park
Visualization and inference based on wavelet coefficients, SiZer and SiNos. Comput. Stat. Data Anal. 51(12): 5994-6012 (2007) - [j5]Yufeng Liu, Hao Helen Zhang, Cheolwoo Park
Support vector machines with adaptive Lq penalty. Comput. Stat. Data Anal. 51(12): 6380-6394 (2007) - 2006
- [j4]Hao Helen Zhang
Gene selection using support vector machines with non-convex penalty. Bioinform. 22(1): 88-95 (2006) - [j3]Stilian Stoev, Murad S. Taqqu, Cheolwoo Park
LASS: a tool for the local analysis of self-similarity. Comput. Stat. Data Anal. 50(9): 2447-2471 (2006) - [c1]Cheolwoo Park, H. Shen, J. S. Marron, Félix Hernández-Campos, Darryl Veitch:
Capturing the Elusive Poissonity in Web Traffic. MASCOTS 2006: 189-196 - 2005
- [j2]Cheolwoo Park
Long-range dependence in a changing Internet traffic mix. Comput. Networks 48(3): 401-422 (2005) - [j1]Stilian Stoev, Murad S. Taqqu, Cheolwoo Park
On the wavelet spectrum diagnostic for Hurst parameter estimation in the analysis of Internet traffic. Comput. Networks 48(3): 423-445 (2005)
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last updated on 2024-08-29 21:52 CEST by the dblp team
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