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Related papers: Projections and Phase retrieval

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In this paper we tackle the problem of recovering the phase of complex linear measurements when only magnitude information is available and we control the input. We are motivated by the recent development of dedicated optics-based hardware…

Machine Learning · Computer Science 2020-02-17 Sidharth Gupta , Rémi Gribonval , Laurent Daudet , Ivan Dokmanić

Creating virtual models of real spaces and objects is cumbersome and time consuming. This paper focuses on the problem of geometric reconstruction from sparse data obtained from certain image-based modeling approaches. A number of elegant…

Computational Geometry · Computer Science 2010-03-19 Eleanor G. Rieffel , Don Kimber , Jim Vaughan

This paper deals with developing techniques for the reconstruction of high-dimensional datasets given each bivariate projection, as would be found in a matrix scatterplot. A graph-based solution is introduced, involving clique-finding,…

Machine Learning · Computer Science 2023-12-27 Eli Dugan , Klaus Mueller

Graphs are a powerful tool for analyzing large data sets, but many real-world phenomena involve interactions that go beyond the simple pairwise relationships captured by a graph. In this paper we introduce and study a simple combinatorial…

Data Structures and Algorithms · Computer Science 2025-11-25 Elise Tate , Joshua A. Grochow

We propose a new approach for constructing a 3D representation from a 2D wireframe drawing. A drawing is simply a parallel projection of a 3D object onto a 2D surface; humans are able to recreate mental 3D models from 2D representations…

Computer Vision and Pattern Recognition · Computer Science 2010-07-16 Kyle Johnson , Clayton Chang , Hod Lipson

Interesting data often concentrate on low dimensional smooth manifolds inside a high dimensional ambient space. Random projections are a simple, powerful tool for dimensionality reduction of such data. Previous works have studied bounds on…

Machine Learning · Statistics 2016-09-13 Subhaneil Lahiri , Peiran Gao , Surya Ganguli

Contours may be viewed as the 2D outline of the image of an object. This type of data arises in medical imaging as well as in computer vision and can be modeled as data on a manifold and can be studied using statistical shape analysis.…

Applications · Statistics 2017-05-17 Chalani Prematilake , Leif Ellingson

We construct a new kind of measures, called projection families, which generalize the classical notion of vector and operator-valued measures. The maximal class of reasonable functions admits an integral with respect to a projection family,…

Functional Analysis · Mathematics 2025-10-15 Luis A. Cedeño-Pérez , Hernando Quevedo

In 1994, John Cobb asked: given $N>m>k>0$, does there exist a Cantor set in $\mathbb R^N$ such that each of its projections into $m$-planes is exactly $k$-dimensional? Such sets were described for $(N,m,k)=(2,1,1)$ by L.Antoine (1924) and…

Geometric Topology · Mathematics 2022-12-07 Olga Frolkina

This paper considers the problem of robust subspace recovery: given a set of $N$ points in $\mathbb{R}^D$, if many lie in a $d$-dimensional subspace, then can we recover the underlying subspace? We show that Tyler's M-estimator can be used…

Machine Learning · Statistics 2021-04-30 Teng Zhang

We consider the problem of conjugate phase retrieval in Paley-Wiener space $PW_{\pi}$. The goal of conjugate phase retrieval is to recover a signal $f$ from the magnitudes of linear measurements up to unknown phase factor and unknown…

Information Theory · Computer Science 2019-10-30 Chun-Kit Lai , Friedrich Littmann , Eric Weber

We study the method of cyclic projections when applied to closed and linear subspaces $M_i$, $i=1,\ldots,m$, of a real Hilbert space $\mathcal H$. We show that the average distance to individual sets enjoys a polynomial behaviour…

Optimization and Control · Mathematics 2023-04-18 Simeon Reich , Rafał Zalas

Tensor completion recovers a multi-dimensional array from a limited number of measurements. Using the recently proposed tensor ring (TR) decomposition, in this paper we show that a d-order tensor of dimensional size n and TR rank r can be…

Machine Learning · Computer Science 2020-03-17 Huyan Huang , Yipeng Liu , Ce Zhu

X-ray phase-contrast imaging has the potential to improve image contrast with lower dose by probing an object's refractive properties as well as its absorptive properties. To reconstruct a phase-contrast image from a raw dataset, a phase…

Medical Physics · Physics 2025-08-19 Giavanna Jadick , Patrick La Rivière

Reconstructing a 3D object from a 2D image is a well-researched vision problem, with many kinds of deep learning techniques having been tried. Most commonly, 3D convolutional approaches are used, though previous work has shown…

Computer Vision and Pattern Recognition · Computer Science 2023-02-17 Rohan Agarwal , Wei Zhou , Xiaofeng Wu , Yuhan Li

We give upper bounds on the number of exceptional radial projections of arbitrary subsets of vector spaces over finite fields. Our bounds do not depend on the dimension of the ambient space. Let $\mathbb{F}_q^d$ be the $d$-dimensional…

Combinatorics · Mathematics 2025-12-01 Paige Bright , Ben Lund , Thang Pham

Critical loci for projective reconstruction from three views in four dimensional projective space are defined by an ideal generated by maximal minors of suitable $4 \times 3$ matrices, $N,$ of linear forms. Such loci are classified in this…

Algebraic Geometry · Mathematics 2019-02-04 Marina Bertolini , GianMario Besana , Roberto Notari , Cristina Turrini

In our article we consider some algebraical methods which may be useful in some inverse spectral problems. The reconstraction of the matrix from its minors is considered.

Commutative Algebra · Mathematics 2007-05-23 A. V. Mouftakhov

Unknown-view tomography (UVT) reconstructs a 3D density map from its 2D projections at unknown, random orientations. A line of work starting with Kam (1980) employs the method of moments (MoM) with rotation-invariant Fourier features to…

Optimization and Control · Mathematics 2023-06-13 Shuai Huang , Mona Zehni , Ivan Dokmanić , Zhizhen Zhao

Matrix polynomials given in an orthogonal basis are considered. Following the ideas of Mackey et al. "Vector spaces of Linearizations for Matrix Polynomials" (2006), the vec- tor spaces, called M1(P), M2(P) and DM(P), of potential…

Rings and Algebras · Mathematics 2017-03-03 Heike Faßbender , Philip Saltenberger