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In Gaussian graphical model selection, noise-corrupted samples present significant challenges. It is known that even minimal amounts of noise can obscure the underlying structure, leading to fundamental identifiability issues. A recent line…

Machine Learning · Statistics 2024-05-09 Abrar Zahin , Rajasekhar Anguluri , Lalitha Sankar , Oliver Kosut , Gautam Dasarathy

We propose a model for recoverable robust optimization with commitment. Given a combinatorial optimization problem and uncertainty about elements that may fail, we ask for a robust solution that, after the failing elements are revealed, can…

Data Structures and Algorithms · Computer Science 2023-06-16 Felix Hommelsheim , Nicole Megow , Komal Muluk , Britta Peis

Observability is a fundamental concept in system inference and estimation. This paper is focused on structural observability analysis of Cartesian product networks. Cartesian product networks emerge in variety of applications including in…

Systems and Control · Electrical Eng. & Systems 2020-01-15 Mohammadreza Doostmohammadian

We consider the problem of completing a matrix with categorical-valued entries from partial observations. This is achieved by extending the formulation and theory of one-bit matrix completion. We recover a low-rank matrix $X$ by maximizing…

Numerical Analysis · Computer Science 2015-07-03 Yang Cao , Yao Xie

We propose a penalized pseudo-likelihood criterion to estimate the graph of conditional dependencies in a discrete Markov random field that can be partially observed. We prove the convergence of the estimator in the case of a finite or…

Methodology · Statistics 2022-09-05 Florencia Leonardi , Rodrigo R. S. Carvalho

A variety of information processing tasks in practice involve recovering $n$ objects from single-shot graph-based measurements, particularly those taken over the edges of some measurement graph $\mathcal{G}$. This paper concerns the…

Information Theory · Computer Science 2016-08-04 Yuxin Chen , Andrea J. Goldsmith

This paper deals with strong structural controllability of linear systems. In contrast to existing work, the structured systems studied in this paper have a so-called zero/nonzero/arbitrary structure, which means that some of the entries…

Optimization and Control · Mathematics 2019-03-11 Jiajia Jia , Henk J. van Waarde , Harry L. Trentelman , M. Kanat Camlibel

We consider the recovery of a continuous domain piecewise constant image from its non-uniform Fourier samples using a convex matrix completion algorithm. We assume the discontinuities/edges of the image are localized to the zero levelset of…

Information Theory · Computer Science 2018-02-14 Greg Ongie , Sampurna Biswas , Mathews Jacob

Recovery of the sparsity pattern (or support) of an unknown sparse vector from a limited number of noisy linear measurements is an important problem in compressed sensing. In the high-dimensional setting, it is known that recovery with a…

Information Theory · Computer Science 2012-06-26 Galen Reeves , Michael Gastpar

This paper addresses the blind recovery of the parity check matrix of an (n,k) linear block code over noisy channels by proposing a fast recovery scheme consisting of 3 parts. Firstly, this scheme performs initial error position detection…

Information Theory · Computer Science 2023-05-09 Peng Wang , Yong Liang Guan , Lipo Wang , Peng Cheng

In this paper, we study the zero-error capacity of channels with memory, which are represented by graphs. We provide a method to construct code for any graph with one edge, thereby determining a lower bound on its zero-error capacity.…

Information Theory · Computer Science 2024-06-26 Qi Cao , Qi Chen , Baoming Bai

In this work, we consider the list-decodability and list-recoverability of codes in the zero-rate regime. Briefly, a code $\mathcal{C} \subseteq [q]^n$ is $(p,\ell,L)$-list-recoverable if for all tuples of input lists $(Y_1,\dots,Y_n)$ with…

Information Theory · Computer Science 2023-09-06 Nicolas Resch , Chen Yuan , Yihan Zhang

Large language models confidently produce outdated answers, and no existing method can detect them. We show this is not an engineering failure but a structural one: temporal drift, whether a stored fact has changed since training, is…

Artificial Intelligence · Computer Science 2026-05-12 Rania Elbadry , Ahmed Heakl , Fan Zhang , Dani Bouch , Yuxia Wang , Preslav Nakov , Zhuohan Xie

Locally repairable codes (LRCs) are error correcting codes used in distributed data storage. A traditional approach is to look for codes which simultaneously maximize error tolerance and minimize storage space consumption. However, this…

Information Theory · Computer Science 2015-12-21 Antti Pöllänen

We consider the problem of learning a graph modeling the statistical relations of the $d$ variables from a dataset with $n$ samples $X \in \mathbb{R}^{n \times d}$. Standard approaches amount to searching for a precision matrix $\Theta$…

Machine Learning · Statistics 2023-12-13 Titouan Vayer , Etienne Lasalle , Rémi Gribonval , Paulo Gonçalves

The group synchronization problem is to estimate unknown group elements at the vertices of a graph when given a set of possibly noisy observations of group differences at the edges. We consider the group synchronization problem on finite…

Statistics Theory · Mathematics 2022-05-24 Bradley Stich

A graph is reconstructible if it is determined up to isomorphism from the collection of all its one-vertex-deleted subgraphs, known as the deck of G. The Reconstruction Conjecture (RC) posits that every finite simple graph with at least…

Combinatorics · Mathematics 2026-01-05 J. Antony Aravind , S. Monikandan

This note formulates a deterministic recovery result for vectors $x$ from quadratic measurements of the form $(Ax)_i \overline{(Ax)_j}$ for some left-invertible $A$. Recovery is exact, or stable in the noisy case, when the couples $(i,j)$…

Numerical Analysis · Mathematics 2018-01-16 Laurent Demanet , Vincent Jugnon

Fault tolerance is a major concern in distributed computational settings. In the classic master-worker setting, a server (the master) needs to perform some heavy computation which it may distribute to $m$ other machines (workers) in order…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-10-30 Keren Censor-Hillel , Yuka Machino , Pedro Soto

Graph alignment refers to the task of finding the vertex correspondence between two correlated graphs of $n$ vertices. Extensive study has been done on polynomial-time algorithms for the graph alignment problem under the Erd\H{o}s-R\'enyi…

Data Structures and Algorithms · Computer Science 2024-06-12 Ziao Wang , Weina Wang , Lele Wang