ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1302.4607
  4. Cited By
Asymptotic optimality and efficient computation of the leave-subject-out
  cross-validation

Asymptotic optimality and efficient computation of the leave-subject-out cross-validation

19 February 2013
Ganggang Xu
Jianhua Z. Huang
ArXiv (abs)PDFHTML

Papers citing "Asymptotic optimality and efficient computation of the leave-subject-out cross-validation"

8 / 8 papers shown
Risk and cross validation in ridge regression with correlated samples
Risk and cross validation in ridge regression with correlated samples
Alexander B. Atanasov
Jacob A. Zavatone-Veth
Cengiz Pehlevan
586
8
0
08 Aug 2024
Locally Adaptive and Differentiable Regression
Locally Adaptive and Differentiable RegressionJournal of Machine Learning for Modeling and Computing (JMLMC), 2023
Mingxuan Han
Varun Shankar
J. M. Phillips
Chenglong Ye
323
2
0
14 Aug 2023
On the Asymptotic Optimality of Cross-Validation based Hyper-parameter
  Estimators for Regularized Least Squares Regression Problems
On the Asymptotic Optimality of Cross-Validation based Hyper-parameter Estimators for Regularized Least Squares Regression Problems
Biqiang Mu
Tianshi Chen
L. Ljung
136
6
0
21 Apr 2021
Solar: $L_0$ solution path averaging for fast and accurate variable
  selection in high-dimensional data
Solar: L0L_0L0​ solution path averaging for fast and accurate variable selection in high-dimensional data
Ning Xu
Timothy C. G. Fisher
250
0
0
30 Jul 2020
Nonparametric Inference under B-bits Quantization
Nonparametric Inference under B-bits Quantization
Kexuan Li
Ruiqi Liu
Ganggang Xu
Zuofeng Shang
MQ
204
0
0
24 Jan 2019
Fast Covariance Estimation for Multivariate Sparse Functional Data
Fast Covariance Estimation for Multivariate Sparse Functional Data
Cai Li
Luo Xiao
S. Luo
128
50
0
03 Dec 2018
Comparative evaluation of state-of-the-art algorithms for SSVEP-based
  BCIs
Comparative evaluation of state-of-the-art algorithms for SSVEP-based BCIs
V. Oikonomou
G. Liaros
Kostantinos Georgiadis
E. Chatzilari
Katerina Adam
S. Nikolopoulos
Y. Kompatsiaris
153
61
0
02 Feb 2016
A universal approximate cross-validation criterion and its asymptotic
  distribution
A universal approximate cross-validation criterion and its asymptotic distributionThe International Journal of Biostatistics (Int J Biostat), 2012
Daniel Commenges
C. Proust-Lima
C. Samieri
Benoit Liquet
215
10
0
08 Jun 2012
1
Page 1 of 1