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We present a sampling theory for a class of binary images with finite rate of innovation (FRI). Every image in our model is the restriction of $\mathds{1}_{\{p\leq0\}}$ to the image plane, where $\mathds{1}$ denotes the indicator function…

Computational Geometry · Computer Science 2016-11-03 Mitra Fatemi , Arash Amini , Martin Vetterli

Backgrounds in images play a major role in contributing to spurious correlations among different data points. Owing to aesthetic preferences of humans capturing the images, datasets can exhibit positional (location of the object within a…

Computer Vision and Pattern Recognition · Computer Science 2025-09-09 Mishal Fatima , Steffen Jung , Margret Keuper

The aim of this paper is to investigate properties preserved and co-preserved by coarsely $n$-to-1 functions, in particular by the quotient maps $X\to X/\sim$ induced by a finite group $G$ acting by isometries on a metric space $X$. The…

Metric Geometry · Mathematics 2016-02-24 Jerzy Dydak , Ziga Virk

Many tasks in image processing can be tackled by modeling an appropriate data fidelity term $\Phi: \mathbb{R}^n \rightarrow \mathbb{R} \cup \{+\infty\}$ and then solve one of the regularized minimization problems \begin{align*}…

Optimization and Control · Mathematics 2015-06-30 René Ciak

Some versions of quantum theory treat wave function collapse as a fundamental physical phenomenon to be described by explicit laws. One motivation is to find a consistent unification of quantum theory and gravity, in which collapse prevents…

Quantum Physics · Physics 2019-07-17 Adrian Kent

In this paper we consider the problem of finding the {\em densest} subset subject to {\em co-matroid constraints}. We are given a {\em monotone supermodular} set function $f$ defined over a universe $U$, and the density of a subset $S$ is…

Data Structures and Algorithms · Computer Science 2012-07-31 Venkatesan T. Chakaravarthy , Natwar Modani , Sivaramakrishnan R. Natarajan , Sambuddha Roy , Yogish Sabharwal

Many computer vision and medical imaging problems are faced with learning from large-scale datasets, with millions of observations and features. In this paper we propose a novel efficient learning scheme that tightens a sparsity constraint…

Machine Learning · Statistics 2017-02-07 Adrian Barbu , Yiyuan She , Liangjing Ding , Gary Gramajo

To reduce the x-ray dose in computerized tomography (CT), many constrained optimization approaches have been proposed aiming at minimizing a regularizing function that measures lack of consistency with some prior knowledge about the object…

Medical Physics · Physics 2017-04-05 Edgar Garduño , Gabor T. Herman

Removing undesired reflections from images taken through the glass is of great importance in computer vision. It serves as a means to enhance the image quality for aesthetic purposes as well as to preprocess images in machine learning and…

Computer Vision and Pattern Recognition · Computer Science 2019-05-13 Yang Yang , Wenye Ma , Yin Zheng , Jian-Feng Cai , Weiyu Xu

Recently, sparsity-based algorithms are proposed for super-resolution spectrum estimation. However, to achieve adequately high resolution in real-world signal analysis, the dictionary atoms have to be close to each other in frequency,…

Machine Learning · Statistics 2015-06-05 Yiyuan She , Huanghuang Li , Jiangping Wang , Dapeng Wu

In this expository paper, we consider the problem of causal inference and efficient estimation for the counterfactual survivor function. This problem has previously been considered in the literature in several papers, each relying on the…

Methodology · Statistics 2025-10-02 Benjamin R. Baer , Ashkan Ertefaie , Robert L. Strawderman

In x-ray computed tomography (CT) it is generally acknowledged that reconstruction methods exploiting image sparsity allow reconstruction from a significantly reduced number of projections. The use of such reconstruction methods is…

Numerical Analysis · Mathematics 2014-08-05 Jakob S. Jørgensen , Emil Y. Sidky , Per Christian Hansen , Xiaochuan Pan

We consider a minimization problem whose objective function is the sum of a fidelity term, not necessarily convex, and a regularization term defined by a positive regularization parameter $\lambda$ multiple of the $\ell_0$ norm composed…

Optimization and Control · Mathematics 2021-11-17 Yuesheng Xu

Image registration is a widespread problem which applies models about image transformation or image similarity to align discrete images of the same scene. Nevertheless, the theoretical limits on its accuracy are not understood even in the…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Serap A. Savari

Sample size criteria are often expressed in terms of the concentration of the posterior density, as controlled by some sort of error bound. Since this is done pre-experimentally, one can regard the posterior density as a function of the…

Statistics Theory · Mathematics 2007-06-13 B. Clarke , Ao Yuan

The indeterminism of quantum mechanics generally permits the independent specification of both an initial and a final condition on the state. Quantum pre-and-post-selection of states opens up a new, experimentally testable, sector of…

Quantum Physics · Physics 2015-06-17 Paul Davies

In a companion paper [quant-ph/9904013] we have investigated several variations of Schwinger's proposed mechanism for sonoluminescence. We demonstrated that any realistic version of Schwinger's mechanism must depend on extremely rapid…

Quantum Physics · Physics 2009-10-31 Stefano Liberati , Matt Visser , Francesco Belgiorno , Dennis Sciama

The property that a one to one function from the natural numbers to itself preserves the density of sub-sets is shown to be equivalent to a condition on the covering of intervals in the range of the function by images of intervals in the…

General Mathematics · Mathematics 2007-05-23 Paul J. Huizinga

We study infinite systems of particles which undergo coalescence and fragmentation, in a manner determined solely by their masses. A pair of particles having masses $x$ and $y$ coalesces at a given rate $K(x,y)$. A particle of mass $x$…

Probability · Mathematics 2015-08-07 Eduardo Cepeda

We study diffusion-controlled single-species annihilation with sparse initial conditions. In this random process, particles undergo Brownian motion, and when two particles meet, both disappear. We focus on sparse initial conditions where…

Statistical Mechanics · Physics 2016-11-23 E. Ben-Naim , P. L. Krapivsky
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