Sparse pca - Open Access .click

Results 21 to 30 of about 25,940 (257)

A Literature Review of (Sparse) Exponential Family PCA [PDF]

Journal of Statistical Theory and Practice, 2022
AbstractThis is a brief overview of the methodology around exponential family PCA. We revisit classic PCA methodology, and we focus on exponential family PCA due to its applicability on a number of distributions and hence a wide variety of problems.
Luke Smallman, Andreas Artemiou
openaire +3 more sources

Sparse PCA on fixed-rank matrices [PDF]

Mathematical Programming, 2022
Sparse PCA is the optimization problem obtained from PCA by adding a sparsity constraint on the principal components. Sparse PCA is NP-hard and hard to approximate even in the single-component case. In this paper we settle the computational complexity of sparse PCA with respect to the rank of the covariance matrix.
openaire +3 more sources

Probabilistic power flow calculation using principal component analysis-based compressive sensing

Frontiers in Energy Research, 2023
The increasing scale of the injection of renewable energy has brought about great uncertainty to the operation of power grid. In this situation, probabilistic power flow (PPF) calculation has been introduced to mitigate the low accuracy of traditional ...
Tonghe Wang +4 more
doaj +1 more source

Performing Sparse Regularization and Dimension Reduction Simultaneously in Multimodal Data Fusion

Frontiers in Neuroscience, 2019
Collecting multiple modalities of neuroimaging data on the same subject is increasingly becoming the norm in clinical practice and research. Fusing multiple modalities to find related patterns is a challenge in neuroimaging analysis.
Zhengshi Yang +539 more
doaj +1 more source

Sparse PCA from Sparse Linear Regression

CoRR, 2018
To appear in NeurIPS ...
Bresler, Guy, Park, Sung Min, Persu, Madalina +2 more
openaire +4 more sources

A Survey on Nonconvex Regularization-Based Sparse and Low-Rank Recovery in Signal Processing, Statistics, and Machine Learning

IEEE Access, 2018
In the past decade, sparse and low-rank recovery has drawn much attention in many areas such as signal/image processing, statistics, bioinformatics, and machine learning.
Fei Wen, Lei Chu, Peilin Liu, Robert C. Qiu +3 more
doaj +1 more source

A Randomized Rounding Algorithm for Sparse PCA [PDF]

ACM Transactions on Knowledge Discovery from Data, 2017
We present and analyze a simple, two-step algorithm to approximate the optimal solution of the sparse PCA problem. In the proposed approach, we first solve an ℓ 1 -penalized version of the NP-hard sparse PCA optimization problem and then we use a randomized rounding strategy to sparsify the resulting dense solution.
Kimon Fountoulakis +3 more
openaire +2 more sources

Face Recognition Based on Sparse Two-Direction Two-Dimensional Principle Component Analysis [PDF]

Jisuanji gongcheng, 2019
Two-Direction Two-Dimensional Principle Component Analysis((2D)2PCA) is an improved method of Principle Component Analysis(PCA) in the two-dimensional space.However,just like PCA,the (2D)2PCA is susceptible to abnormal values,its robustness is weak and ...
ZHANG Yuping, GONG Xiaofeng, LUO Ruisen
doaj +1 more source

NP-hardness and inapproximability of sparse PCA [PDF]

Information Processing Letters, 2017
We give a reduction from {\sc clique} to establish that sparse PCA is NP-hard. The reduction has a gap which we use to exclude an FPTAS for sparse PCA (unless P=NP). Under weaker complexity assumptions, we also exclude polynomial constant-factor approximation algorithms.
openaire +3 more sources

A greedy anytime algorithm for sparse PCA

CoRR, 2019
The taxing computational effort that is involved in solving some high-dimensional statistical problems, in particular problems involving non-convex optimization, has popularized the development and analysis of algorithms that run efficiently (polynomial-time) but with no general guarantee on statistical consistency.
Guy Holtzman, Adam Soffer, Dan Vilenchik
openaire +3 more sources

fos: computer and information sciences
machine learning stat.ml
machine learning cs.lg

statistics - machine learning
computer science - machine learning
fos: mathematics

statistics theory math.st
mathematics - statistics theory
principal component analysis