Results 21 to 30 of about 582,597 (232)
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
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Photoacoustic Reconstruction Using Sparsity in Curvelet Frame: Image Versus Data Domain [PDF]
IEEE Transactions on Computational Imaging, 2020 Curvelet frame is of special significance for photoacoustic tomography (PAT) due to its sparsifying and microlocalisation properties. We derive a one-to-one map between wavefront directions in image and data spaces in PAT which suggests near equivalence ...
Bolin Pan +7 more
semanticscholar +1 more source
Learning physically consistent differential equation models from data using group sparsity.
Physical Review E, 2021 We propose a statistical learning framework based on group-sparse regression that can be used to (i) enforce conservation laws, (ii) ensure model equivalence, and (iii) guarantee symmetries when learning or inferring differential-equation models from ...
S. Maddu +3 more
semanticscholar +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
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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
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An Equivalence between the Lasso and Support Vector Machines [PDF]
arXiv.org, 2013 We investigate the relation of two fundamental tools in machine learning and signal processing, that is the support vector machine (SVM) for classification, and the Lasso technique used in regression.
Martin Jaggi
semanticscholar +1 more source
PLoS ONE, 2018 We proposed a new efficient image denoising scheme, which mainly leads to four important contributions whose approaches are different from existing ones.
Shuting Cai +5 more
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Learning Markov Equivalence Classes of Directed Acyclic Graphs: An Objective Bayes Approach
Bayesian Analysis, 2018 . A Markov equivalence class contains all the Directed Acyclic Graphs (DAGs) encoding the same conditional independencies, and is represented by a Completed Partially Directed Acyclic Graph (CPDAG), also named Essential Graph (EG).
F. Castelletti +3 more
semanticscholar +1 more source
Asymptotic equivalence of quantum state tomography and noisy matrix completion [PDF]
, 2013 Matrix completion and quantum tomography are two unrelated research areas with great current interest in many modern scientific studies. This paper investigates the statistical relationship between trace regression in matrix completion and quantum state ...
Yazhen Wang
semanticscholar +1 more source
Design of robust constant beamwidth beamformer with maximal sparsity
Tongxin xuebao, 2015 To reduce the complexity of broadband array systems,an optimization model was built based on the analysis of the sparsity of the broadband array.The objective function was the convex combination of sensor and TDL sparsity with the constraint of constant ...
Kai WU, Tao SU, Qiang LI, Xue-hui HE
doaj +2 more sources