$NP/CLP$ Equivalence: A Phenomenon Hidden Among Sparsity Models for Information Processing
, 2015 submitted to IEEE Transactions on Information Theory in June ...
Peng, Jigen, Yue, Shigang, Li, Haiyang
openaire +4 more sources
Sparsity Equivalence of Anisotropic Decompositions
, 2011 Anisotropic decompositions using representation systems such as curvelets, contourlet, or shearlets have recently attracted significantly increased attention due to the fact that they were shown to provide optimally sparse approximations of functions exhibiting singularities on lower dimensional embedded manifolds.
Gitta Kutyniok
openaire +4 more sources
SHAPE RECONSTRUCTION VIA EQUIVALENCE PRINCIPLES,CONSTRAINED INVERSE SOURCE PROBLEMS AND SPARSITY PROMOTION [PDF]
Progress In Electromagnetics Research, 2017 A new approach for position and shape reconstruction of both penetrable and impenetrable objects from the measurements of the scattered fields is introduced and described. The approach takes advantage of the fact that for perfect electric conductors the induced currents are localized on the boundary, and equivalent sources also placed on the surface of
Martina T. Bevacqua, Tommaso Isernia
openaire +4 more sources
$NP/CMP$ Equivalence: A Phenomenon Hidden Among Sparsity Models $l_{0}$ Minimization and $l_{p}$ Minimization for Information Processing [PDF]
IEEE Transactions on Information Theory, 2015 In this paper, we have proved that in every underdetermined linear system $Ax=b$ , there corresponds a constant $p^{*}(A,b)>0$ such that every solution to the $l_{p}$ -norm minimization problem also solves the $l_{0}$ -norm minimization problem whenever $0 . This phenomenon is named $NP/CMP$ equivalence.
Jigen Peng, Shigang Yue, Haiyang Li
openaire +3 more sources
A Greedy Algorithm To Extract Sparsity Degree For L1/L0-Equivalence In A Deterministic Context
, 2012 Publication in the conference proceedings of EUSIPCO, Bucharest, Romania ...
Pustelnik, Nelly +4 more
openaire +5 more sources
Remote Sensing, 2023 Hyperspectral image (HSI) super-resolution is a vital technique that generates high spatial-resolution HSI (HR-HSI) by integrating information from low spatial-resolution HSI with high spatial-resolution multispectral image (MSI).
Yidong Peng +3 more
doaj +1 more source
Sparsest Univariate Learning Models Under Lipschitz Constraint
IEEE Open Journal of Signal Processing, 2022 Beside the minimizationof the prediction error, two of the most desirable properties of a regression scheme are stability and interpretability. Driven by these principles, we propose continuous-domain formulations for one-dimensional regression problems.
Shayan Aziznejad +2 more
doaj +1 more source
Debiased inference for heterogeneous subpopulations in a high-dimensional logistic regression model
Scientific Reports, 2023 Due to the prevalence of complex data, data heterogeneity is often observed in contemporary scientific studies and various applications. Motivated by studies on cancer cell lines, we consider the analysis of heterogeneous subpopulations with binary ...
Hyunjin Kim, Eun Ryung Lee, Seyoung Park
doaj +1 more source
Qualitative Methods for the Inverse Obstacle Problem: A Comparison on Experimental Data
Journal of Imaging, 2019 Qualitative methods are widely used for the solution of inverse obstacle problems. They allow one to retrieve the morphological properties of the unknown targets from the scattered field by avoiding dealing with the problem in its full non-linearity and ...
Martina T. Bevacqua, Roberta Palmeri
doaj +1 more source
An Interpretable and Scalable Recommendation Method Based on Network Embedding
IEEE Access, 2019 Matrix factorization is a widely used technique in recommender systems. However, its performance is often affected by the sparsity and the scalability. To address the above-mentioned problem, we propose an interpretable and scalable recommendation method
Xuejian Zhang +4 more
doaj +1 more source