신승준 프로필 사진

신승준

Shin, Seung Jun

정경대학

통계학과

자료 필터

자료유형

발행연도

2007 ~ 2026
2007 2026

키워드

언어

선택된 필터

  • article
  • conference
  • book

전체 75건 중 1번부터 10번까지의 결과를 표시합니다.

2026
Article

roclab: An R package for ROC-optimizing binary classification

  • 2026-06
  • SoftwareX
  • ELSEVIER
Article

Variable selection in AUC-optimizing classification

  • 2026-01
  • Computational Statistics and Data Analysis
  • Elsevier B.V.
2025
Article

Scaling Up ROC-Optimizing Support Vector Machines

  • 2025-12-03
  • STAT
  • WILEY
Article

PERSONALIZED RISK PREDICTION FOR CANCER SURVIVORS: A GENERALIZED BAYESIAN SEMIPARAMETRIC MODEL OF RECURRENT EVENTS WITH COMPETING OUTCOMES

  • Nguyen, Nam Hoai ; 
  • Shin, Seung Jun ; 
  • Dodd-eaton, Elissa B. ; 
  • Ning, Jing ; 
  • Wang, Wenyi
  • 2025-12
  • Annals of Applied Statistics
  • INST MATHEMATICAL STATISTICS-IMS
Article

Lower rank linearization for scalable training of kernel machines

  • 2025-11
  • Communications for Statistical Applications and Methods
  • Korean Statistical Society
Article

A least distance estimator for a multivariate regression model using deep neural networks

  • 2025-04-16
  • Journal of Statistical Computation and Simulation
  • TAYLOR & FRANCIS LTD
2024
Article

Personalized prediction of survival rate with combination of penalized Cox models in patients with colorectal cancer

  • 2024-06-14
  • Medicine
  • LIPPINCOTT WILLIAMS & WILKINS
Article

Crowd-sourced benchmarking of single-sample tumor subclonal reconstruction

  • Salcedo, Adriana ; 
  • Tarabichi, Maxime ; 
  • Buchanan, Alex ; 
  • Espiritu, Shadrielle M. G. ; 
  • Zhang, Hongjiu ; 
  • ... Shin, Seung Jun ; 
  • 외 94명
  • 2024-06
  • Nature Biotechnology
  • Nature Research
Article

Simultaneous estimation and variable selection for a non-crossing multiple quantile regression using deep neural networks

  • 2024-06
  • Statistics and Computing
  • SPRINGER
Article

A concise overview of principal support vector machines and its generalization

  • 2024-04
  • Communications for Statistical Applications and Methods
  • 한국통계학회
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