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Covariance matrix reconstruction is a topic of great significance in the field of one-bit signal processing and has numerous practical applications. Despite its importance, the conventional arcsine law with zero threshold is incapable of…

Signal Processing · Electrical Eng. & Systems 2023-03-30 Yu-Hang Xiao , Lei Huang , David Ramírez , Cheng Qian , Hing Cheung So

The source-coding problem with side information at the decoder is studied subject to a constraint that the encoder---to whom the side information is unavailable---be able to compute the decoder's reconstruction sequence to within some…

Information Theory · Computer Science 2016-11-15 Amos Lapidoth , Andreas Malär , Michèle Wigger

We propose an embarrassingly simple but very effective scheme for high-quality dense stereo reconstruction: (i) generate an approximate reconstruction with your favourite stereo matcher; (ii) rewarp the input images with that approximate…

Computer Vision and Pattern Recognition · Computer Science 2021-06-21 Corinne Stucker , Konrad Schindler

We investigate the sparse recovery problem of reconstructing a high-dimensional non-negative sparse vector from lower dimensional linear measurements. While much work has focused on dense measurement matrices, sparse measurement schemes are…

Information Theory · Computer Science 2009-02-25 M. Amin Khajehnejad , Alexandros G. Dimakis , Weiyu Xu , Babak Hassibi

We consider the problem of learning a discrete distribution in the presence of an $\epsilon$ fraction of malicious data sources. Specifically, we consider the setting where there is some underlying distribution, $p$, and each data source…

Machine Learning · Computer Science 2017-11-23 Mingda Qiao , Gregory Valiant

We consider the zero-error capacity of deletion channels. Specifically, we consider the setting where we choose a codebook ${\cal C}$ consisting of strings of $n$ bits, and our model of the channel corresponds to an adversary who may delete…

Information Theory · Computer Science 2011-02-02 Ian A. Kash , Michael Mitzenmacher , Justin Thaler , Jonathan Ullman

Sparse recovery is widely applied in many fields, since many signals or vectors can be sparsely represented under some frames or dictionaries. Most of fast algorithms at present are based on solving $l^0$ or $l^1$ minimization problems and…

Numerical Analysis · Mathematics 2019-03-06 Chong-Jun Li , Yi-Jun Zhong

With distributed computing and mobile applications becoming ever more prevalent, synchronizing diverging replicas of the same data is a common problem. Reconciliation -- bringing two replicas of the same data structure as close as possible…

Information Theory · Computer Science 2022-08-10 Elod P. Csirmaz , Laszlo Csirmaz

This paper studies the problem of encoding messages into sequences which can be uniquely recovered from some noisy observations about their substrings. The observed reads comprise consecutive substrings with some given minimum overlap. This…

Information Theory · Computer Science 2023-12-11 Hengjia Wei , Moshe Schwartz , Gennian Ge

Worm origin identification and propagation path reconstruction are essential problems in digital forensics. However, a small number of studies have specifically investigated these problems so far. In this paper, we extend a distributed…

Cryptography and Security · Computer Science 2021-08-18 Sara Asgari , Babak Sadeghiyan

We study the classical problem of recovering a multidimensional source signal from observations of nonlinear mixtures of this signal. We show that this recovery is possible (up to a permutation and monotone scaling of the source's original…

Machine Learning · Statistics 2023-01-18 Alexander Schell , Harald Oberhauser

In the semi-streaming model, an algorithm must process any $n$-vertex graph by making one or few passes over a stream of its edges, use $O(n \cdot \text{polylog }n)$ words of space, and at the end of the last pass, output a solution to the…

Data Structures and Algorithms · Computer Science 2025-10-23 Sepehr Assadi , Gary Hoppenworth , Janani Sundaresan

As DNA data storage moves closer to practical deployment, minimizing sequencing coverage depth is essential to reduce both operational costs and retrieval latency. This paper addresses the recently studied Random Access Problem, which…

Information Theory · Computer Science 2026-01-13 Chen Wang , Eitan Yaakobi

An approximate textual retrieval algorithm for searching sources with high levels of defects is presented. It considers splitting the words in a query into two overlapping segments and subsequently building composite regular expressions…

Information Retrieval · Computer Science 2007-05-23 Pere Constans

We consider the problem of stable recovery of sparse signals of the form $$F(x)=\sum_{j=1}^d a_j\delta(x-x_j),\quad x_j\in\mathbb{R},\;a_j\in\mathbb{C}, $$ from their spectral measurements, known in a bandwidth $\Omega$ with absolute error…

Numerical Analysis · Mathematics 2020-01-27 Dmitry Batenkov , Gil Goldman , Yosef Yomdin

We introduce a new phylogenetic reconstruction algorithm which, unlike most previous rigorous inference techniques, does not rely on assumptions regarding the branch lengths or the depth of the tree. The algorithm returns a forest which is…

Populations and Evolution · Quantitative Biology 2011-09-30 Constantinos Daskalakis , Elchanan Mossel , Sebastien Roch

This paper considers the classical error correcting problem which is frequently discussed in coding theory. We wish to recover an input vector $f \in \R^n$ from corrupted measurements $y = A f + e$. Here, $A$ is an $m$ by $n$ (coding)…

Metric Geometry · Mathematics 2007-05-23 Emmanuel Candes , Terence Tao

The sequence reconstruction problem was proposed by Levenshtein in 2001. In this model, a sequence from a code is transmitted over several channels, and the decoder receives the distinct outputs from each channel. The main problem is to…

Information Theory · Computer Science 2025-10-16 Xiang Wang , Han Li , Fang-Wei Fu

Network topology plays a key role in many phenomena, from the spreading of diseases to that of financial crises. Whenever the whole structure of a network is unknown, one must resort to reconstruction methods that identify the least biased…

Data Analysis, Statistics and Probability · Physics 2015-06-09 Rossana Mastrandrea , Tiziano Squartini , Giorgio Fagiolo , Diego Garlaschelli

Suppose that a solution $\widetilde{\mathbf{x}}$ to an underdetermined linear system $\mathbf{b} = \mathbf{A} \mathbf{x}$ is given. $\widetilde{\mathbf{x}}$ is approximately sparse meaning that it has a few large components compared to…

Information Theory · Computer Science 2015-06-29 Mohammadreza Malek-Mohammadi , Cristian R. Rojas , Magnus Jansson , Massoud Babaie-Zadeh