相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。Robust Principal Component Analysis Based On Hypergraph Regularization for Sample Clustering and Co-Characteristic Gene Selection
Ying-Lian Gao et al.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS (2022)
Correntropy-Based Hypergraph Regularized NMF for Clustering and Feature Selection on Multi-Cancer Integrated Data
Na Yu et al.
IEEE TRANSACTIONS ON CYBERNETICS (2021)
Robust principal component analysis: A factorization-based approach with linear complexity
Chong Peng et al.
INFORMATION SCIENCES (2020)
SPARSE PRINCIPAL COMPONENT ANALYSIS VIA VARIABLE PROJECTION
N. Benjamin Erichson et al.
SIAM JOURNAL ON APPLIED MATHEMATICS (2020)
Decoding and encoding (de)mixed population responses
Sander W. Keemink et al.
CURRENT OPINION IN NEUROBIOLOGY (2019)
Distributed coding of choice, action and engagement across the mouse brain
Nicholas A. Steinmetz et al.
NATURE (2019)
Integrative Hypergraph Regularization Principal Component Analysis for Sample Clustering and Co-Expression Genes Network Analysis on Multi-Omics Data
Ming-Juan Wu et al.
IEEE Journal of Biomedical and Health Informatics (2019)
A Parallel Random Forest Algorithm for Big Data in a Spark Cloud Computing Environment
Jianguo Chen et al.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS (2017)
Integrating feature and graph learning with low-rank representation
Chong Peng et al.
NEUROCOMPUTING (2017)
Decomposition into low-rank plus additive matrices for background/foreground separation: A review for a comparative evaluation with a large-scale dataset
Thierry Bouwmans et al.
COMPUTER SCIENCE REVIEW (2017)
Demixed principal component analysis of neural population data
Dmitry Kobak et al.
ELIFE (2016)
A Parallel Patient Treatment Time Prediction Algorithm and Its Applications in Hospital Queuing-Recommendation in a Big Data Environment
Jianguo Chen et al.
IEEE ACCESS (2016)
DeMix: deconvolution for mixed cancer transcriptomes using raw measured data
Jaeil Ahn et al.
BIOINFORMATICS (2013)
Context-dependent computation by recurrent dynamics in prefrontal cortex
Valerio Mante et al.
NATURE (2013)
Neural Correlates of a Decision Variable Before Learning to Perform a Match/Non-Match Task
Xue-Lian Qi et al.
JOURNAL OF NEUROSCIENCE (2012)
A Unified Framework for High-Dimensional Analysis of M-Estimators with Decomposable Regularizers
Sahand N. Negahban et al.
STATISTICAL SCIENCE (2012)
Changes in Prefrontal Neuronal Activity after Learning to Perform a Spatial Working Memory Task
Xue-Lian Qi et al.
CEREBRAL CORTEX (2011)
Stimulus Selectivity in Dorsal and Ventral Prefrontal Cortex after Training in Working Memory Tasks
Travis Meyer et al.
JOURNAL OF NEUROSCIENCE (2011)
Robust Principal Component Analysis?
Emmanuel J. Candes et al.
JOURNAL OF THE ACM (2011)
Power and sample size estimation in microarray studies
Wei-Jiun Lin et al.
BMC BIOINFORMATICS (2010)
Principal component analysis
Herve Abdi et al.
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL STATISTICS (2010)
A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis
Daniela M. Witten et al.
BIOSTATISTICS (2009)
A proximal decomposition method for solving convex variational inverse problems
Patrick L. Combettes et al.
INVERSE PROBLEMS (2008)
Sparse principal component analysis via regularized low rank matrix approximation
Haipeng Shen et al.
JOURNAL OF MULTIVARIATE ANALYSIS (2008)
Neural correlates, computation and behavioural impact of decision confidence
Adam Kepecs et al.
NATURE (2008)
What is principal component analysis?
Markus Ringner
NATURE BIOTECHNOLOGY (2008)
A direct formulation for sparse PCA using semidefinite programming
Alexandre d'Aspremont et al.
SIAM REVIEW (2007)
Representation of spatial goals in rat orbitofrontal cortex
Claudia E. Feierstein et al.
NEURON (2006)
Sparse principal component analysis
Hui Zou et al.
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS (2006)
Regularization and variable selection via the elastic net
H Zou et al.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY (2005)
Optimal sample size for multiple testing:: The case of gene expression microarrays
P Müller et al.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2004)
Timing and neural encoding of somatosensory parametric working memory in macaque prefrontal cortex
CD Brody et al.
CEREBRAL CORTEX (2003)
A modified principal component technique based on the LASSO
IT Jolliffe et al.
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS (2003)
Power and sample size for DNA microarray studies
MLT Lee et al.
STATISTICS IN MEDICINE (2002)
Determination of minimum sample size and discriminatory expression patterns in microarray data
DH Hwang et al.
BIOINFORMATICS (2002)
分享论文
