Selecting the number of components in PCA via random signflips

5 December 2020

Papers citing "Selecting the number of components in PCA via random signflips"

10 / 10 papers shown

Title
ALPCAH: Subspace Learning for Sample-wise Heteroscedastic Data Javier Salazar Cavazos Jeffrey A. Fessler Laura Balzano 31 2 0 12 May 2025
ALPCAH: Sample-wise Heteroscedastic PCA with Tail Singular Value Regularization Javier Salazar Cavazos Jeffrey A. Fessler Laura Balzano 32 1 0 06 Jul 2023
Pursuit of a Discriminative Representation for Multiple Subspaces via Sequential Games Druv Pai Michael Psenka Chih-Yuan Chiu Manxi Wu Yan Sun Yi Ma 24 6 0 18 Jun 2022
Confidence Intervals for the Number of Components in Factor Analysis and Principal Components Analysis via Subsampling Chetkar Jha Ian Barnett 6 0 0 10 May 2022
Closed-Loop Data Transcription to an LDR via Minimaxing Rate Reduction Xili Dai Shengbang Tong Mingyang Li Ziyang Wu Michael Psenka ... Pengyuan Zhai Yaodong Yu Xiaojun Yuan Harry Shum Yi Ma 25 30 0 12 Nov 2021
Consistency of invariance-based randomization tests Yan Sun 35 19 0 25 Apr 2021
Biwhitening Reveals the Rank of a Count Matrix Boris Landa Thomas T. Zhang Y. Kluger 13 21 0 25 Mar 2021
HePPCAT: Probabilistic PCA for Data with Heteroscedastic Noise David Hong Kyle Gilman Laura Balzano Jeffrey A. Fessler 40 19 0 10 Jan 2021
Optimally Weighted PCA for High-Dimensional Heteroscedastic Data David Hong Fan Yang Jeffrey A. Fessler Laura Balzano 16 25 0 30 Oct 2018
Factor modeling for high-dimensional time series: Inference for the number of factors Clifford Lam Q. Yao 49 479 0 04 Jun 2012