Results 31 to 40 of about 90,827 (166)
Sparse PCA from Sparse Linear Regression
CoRR, 2018 To appear in NeurIPS ...
Bresler, Guy +2 more
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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
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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.
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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
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Image Classification Based on Sparse Representation in the Quaternion Wavelet Domain
IEEE Access, 2022 In this study, we propose a novel sparse representation learning method in the Quaternion Wavelet (QW) domain for multi-class image classification. The proposed method takes advantages from: i) the QW decomposition, which promotes sparsity and provides ...
Long H. Ngo +4 more
doaj +1 more source
IEEE Access, 2017 Since microaneurysms (MAs) can be seen as the earliest lesions in diabetic retinopathy, its detection plays a critical role in the diabetic retinopathy diagnosis.
Wei Zhou +4 more
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Extreme Learning Machine Based on Stacked Denoising Sparse Auto-Encoder [PDF]
Jisuanji gongcheng, 2020 Extreme Learning Machine(ELM)randomly selects input weights and hidden-layer bias of network,which increases the complexity and reduces the robustness of network.To address the problem,this paper proposes an ELM algorithm based on stacked Denoising ...
ZHANG Guoling, WANG Xiaodan, LI Rui, LAI Jie, XIANG Qian
doaj +1 more source
Craniofacial similarity analysis through sparse principal component analysis.
PLoS ONE, 2017 The computer-aided craniofacial reconstruction (CFR) technique has been widely used in the fields of criminal investigation, archaeology, anthropology and cosmetic surgery.
Junli Zhao +7 more
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Characteristic gene selection via weighting principal components by singular values. [PDF]
PLoS ONE, 2012 Conventional gene selection methods based on principal component analysis (PCA) use only the first principal component (PC) of PCA or sparse PCA to select characteristic genes.
Jin-Xing Liu +4 more
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