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We consider the maximum coding rate achievable by uniformly-random codes for the deletion channel. We prove an upper bound that's within 0.1 of the best known lower bounds for all values of the deletion probability $d,$ and much closer for…

Information Theory · Computer Science 2022-10-17 Berivan Isik , Francisco Pernice , Tsachy Weissman

Suppose a graph $G$ is stochastically created by uniformly sampling vertices along a line segment and connecting each pair of vertices with a probability that is a known decreasing function of their distance. We ask if it is possible to…

Data Structures and Algorithms · Computer Science 2020-06-09 Yu Chen , Sampath Kannan , Sanjeev Khanna

We study the problem of reconstructing a hidden graph given access to a distance oracle. We design randomized algorithms for the following problems: reconstruction of a degree bounded graph with query complexity $\tilde{O}(n^{3/2})$;…

Data Structures and Algorithms · Computer Science 2013-04-25 Claire Mathieu , Hang Zhou

The problem of string reconstruction from substring information has found many applications due to its relevance in DNA- and polymer-based data storage. One practically important and challenging paradigm requires reconstructing mixtures of…

Information Theory · Computer Science 2020-10-22 Ryan Gabrys , Srilakshmi Pattabiraman , Olgica Milenkovic

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

This paper provides the best bounds to date on the number of randomly sampled entries required to reconstruct an unknown low rank matrix. These results improve on prior work by Candes and Recht, Candes and Tao, and Keshavan, Montanari, and…

Information Theory · Computer Science 2009-10-21 Benjamin Recht

We present a method for the reconstruction of networks, based on the order of nodes visited by a stochastic branching process. Our algorithm reconstructs a network of minimal size that ensures consistency with the data. Crucially, we show…

Data Structures and Algorithms · Computer Science 2010-06-07 Nick Fyson , Tijl De Bie , Nello Cristianini

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

The network unreliability problem asks for the probability that a given undirected graph gets disconnected when every edge independently fails with a given probability $p$. Valiant (1979) showed that this problem is \#P-hard; therefore, the…

Data Structures and Algorithms · Computer Science 2025-04-01 Ruoxu Cen , Jason Li , Debmalya Panigrahi

Positron emission tomography (PET) is widely used in various clinical applications, including cancer diagnosis, heart disease and neuro disorders. The use of radioactive tracer in PET imaging raises concerns due to the risk of radiation…

Computer Vision and Pattern Recognition · Computer Science 2017-12-13 Junshen Xu , Enhao Gong , John Pauly , Greg Zaharchuk

The advancement of sensing technology has driven the widespread application of high-dimensional data. However, issues such as missing entries during acquisition and transmission negatively impact the accuracy of subsequent tasks. Tensor…

Image and Video Processing · Electrical Eng. & Systems 2025-04-09 Jie Yang , Chang Su , Yuhan Zhang , Jianjun Zhu , Jianli Wang

In this paper, we consider recovery of jointly sparse multichannel signals from incomplete measurements. Several approaches have been developed to recover the unknown sparse vectors from the given observations, including thresholding,…

Information Theory · Computer Science 2009-04-06 Yonina C. Eldar , Holger Rauhut

Suppose a given observation matrix can be decomposed as the sum of a low-rank matrix and a sparse matrix (outliers), and the goal is to recover these individual components from the observed sum. Such additive decompositions have…

Machine Learning · Statistics 2010-12-07 Daniel Hsu , Sham M. Kakade , Tong Zhang

In this work we consider the problem of reconstruction of a signal from the magnitude of its Fourier transform, also known as phase retrieval. The problem arises in many areas of astronomy, crystallography, optics, and coherent diffraction…

Optics · Physics 2012-03-22 Eliyahu Osherovich

We consider the problem of estimating the value of MAX-CUT in a graph in the streaming model of computation. At one extreme, there is a trivial $2$-approximation for this problem that uses only $O(\log n)$ space, namely, count the number of…

Data Structures and Algorithms · Computer Science 2018-11-28 Michael Kapralov , Dmitry Krachun

The paper considers the phase retrieval problem in N-dimensional complex vector spaces. It provides two sets of deterministic measurement vectors which guarantee signal recovery for all signals, excluding only a specific subspace and a…

Information Theory · Computer Science 2014-07-21 Volker Pohl , Fanny Yang , Holger Boche

We consider the problem of signal reconstruction for a system under sparse signal corruption by a malicious agent. The reconstruction problem follows the standard error coding problem that has been studied extensively in the literature. We…

Optimization and Control · Mathematics 2023-04-28 Yu Zheng , Olugbenga Moses Anubi , Lalit Mestha , Hema Achanta

In the near future, the Internet of Things will interconnect billions of devices, forming a vast network where users sporadically transmit short messages through multi-path wireless channels. These channels are characterized by the…

Information Theory · Computer Science 2025-05-05 Sajad Daei , Saeed Razavikia , Mikael Skoglund , Gabor Fodor , Carlo Fischione

We consider the following k-sparse recovery problem: design an m x n matrix A, such that for any signal x, given Ax we can efficiently recover x' satisfying ||x-x'||_1 <= C min_{k-sparse} x"} ||x-x"||_1. It is known that there exist…

Data Structures and Algorithms · Computer Science 2011-06-06 Khanh Do Ba , Piotr Indyk , Eric Price , David P. Woodruff

The algorithmic tasks of computing the Hamming distance between a given pattern of length $m$ and each location in a text of length $n$ is one of the most fundamental algorithmic tasks in string algorithms. Unfortunately, there is evidence…

Data Structures and Algorithms · Computer Science 2015-12-15 Tsvi Kopelowitz , Ely Porat