Optimal Convex Lifted Sparse Phase Retrieval and PCA With an Atomic Matrix Norm Regularizer
IEEE Transactions on Information Theory, 2023 We present novel analysis and algorithms for solving sparse phase retrieval and sparse principal component analysis (PCA) with convex lifted matrix formulations. The key innovation is a new mixed atomic matrix norm that, when used as regularization, promotes low-rank matrices with sparse factors.
Andrew D. McRae +2 more
openaire +4 more sources
Tomographic retrieval of cloud liquid water fields from a single scanning microwave radiometer aboard a moving platform – Part 2: Observation system simulation experiments [PDF]
Atmospheric Chemistry and Physics, 2010 Part 1 of this research concluded that many conditions of the 2003 Wakasa Bay experiment were not optimal for the purpose of tomographic retrieval. Part 2 (this paper) then aims to find possible improvements to the mobile cloud tomography method using ...
D. Huang, A. Gasiewski, W. Wiscombe
doaj +1 more source
Journal of Memory and Language, 2020 Abstract There is a long tradition of norming words and other materials for various descriptive properties (e.g., concreteness, emotional valence, imagery, meaningfulness), which allows those properties to be manipulated in memory experiments.
C.J. Brainerd, D.M. Bialer, M. Chang
openaire +2 more sources
Cross-Modal Hashing by
IEEE Access, 2021 With the explosion of multi-modal Web data, effective and efficient techniques are in urgent need for cross-modal data retrieval with relevant semantics.
Dongxiao Ren +3 more
doaj +1 more source
Untrained network regularized by total variation in single-shot lensless holography
Results in Physics, 2023 The optical complex-amplitude (CA) distribution of an object contains rich information, providing insights into the object’s optical characteristics such as retardation and absorption.
Yifan Feng +5 more
doaj +1 more source
Semantic Consistency Cross-Modal Retrieval With Semi-Supervised Graph Regularization
IEEE Access, 2020 Most of the existing cross-modal retrieval methods make use of labeled data to learn projection matrices for different modal data. These methods usually learn the original semantic space to bridge the heterogeneous gap, ignoring the rich semantic ...
Gongwen Xu, Xiaomei Li, Zhijun Zhang
doaj +1 more source
ClothingNet: Cross-Domain Clothing Retrieval With Feature Fusion and Quadruplet Loss
IEEE Access, 2020 Cross-domain clothing retrieval is an active research topic because of its massive potential applications in fashion industry. Due to the large number of garment categories or styles, and different clothing appearances caused by different camera angles ...
Yongwei Miao +4 more
doaj +1 more source
Group Sparsity Penalized Contrast Source Solution Method for 2-D Non-Linear Inverse Scattering
IEEE Open Journal of Antennas and Propagation, 2022 A group sparsity penalized CSI in the wavelet domain is proposed to alleviate ill-posedness within the framework of a contrast-source inversion (CSI) method.
Yarui Zhang +3 more
doaj +1 more source
Convex recovery of a structured signal from independent random linear measurements [PDF]
, 2014 This chapter develops a theoretical analysis of the convex programming method for recovering a structured signal from independent random linear measurements.
D. Amelunxen +20 more
core +3 more sources
Compressive Phase Retrieval From Squared Output Measurements Via Semidefinite Programming [PDF]
, 2012 Given a linear system in a real or complex domain, linear regression aims to recover the model parameters from a set of observations. Recent studies in compressive sensing have successfully shown that under certain conditions, a linear program, namely ...
Balan +24 more
core +1 more source