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We study the problem of learning the causal relationships between a set of observed variables in the presence of latents, while minimizing the cost of interventions on the observed variables. We assume access to an undirected graph $G$ on…

Data Structures and Algorithms · Computer Science 2020-12-29 Raghavendra Addanki , Andrew McGregor , Cameron Musco

We study the problem of deterministic approximate counting of matchings and independent sets in graphs of bounded connective constant. More generally, we consider the problem of evaluating the partition functions of the monomer-dimer model…

Data Structures and Algorithms · Computer Science 2014-10-10 Alistair Sinclair , Piyush Srivastava , Daniel Štefankovič , Yitong Yin

The outage performance of wireless networks with unstructured network topologies is investigated. The network reliability perspective of graph theory is used to obtain the network outage polynomial of generalized wireless networks by…

Information Theory · Computer Science 2019-04-30 Semiha Tedik Basaran , Gunes Karabulut Kurt , Frank R. Kschischang

Sparse recovery can recover sparse signals from a set of underdetermined linear measurements. Motivated by the need to monitor large-scale networks from a limited number of measurements, this paper addresses the problem of recovering sparse…

Information Theory · Computer Science 2015-03-20 Meng Wang , Weiyu Xu , Enrique Mallada , Ao Tang

This paper considers the problem of constructing optimal discriminating experimental designs for competing regression models on the basis of the T-optimality criterion introduced by Atkinson and Fedorov [Biometrika 62 (1975) 57-70].…

Statistics Theory · Mathematics 2014-01-30 Holger Dette , Viatcheslav B. Melas , Petr Shpilev

We revisit the classical problem of optimal experimental design (OED) under a new mathematical model grounded in a geometric motivation. Specifically, we introduce models based on elementary symmetric polynomials; these polynomials capture…

Statistics Theory · Mathematics 2017-05-30 Zelda Mariet , Suvrit Sra

We consider the optimal design problem for a comparison of two regression curves, which is used to establish the similarity between the dose response relationships of two groups. An optimal pair of designs minimizes the width of the…

Methodology · Statistics 2014-11-19 Holger Dette , Kirsten Schorning

We show that any nonzero polynomial in the ideal generated by the $r \times r$ minors of an $n \times n$ matrix $X$ can be used to efficiently approximate the determinant. For any nonzero polynomial $f$ in this ideal, we construct a small…

Computational Complexity · Computer Science 2022-10-28 Robert Andrews , Michael A. Forbes

Modeling biological networks serves as both a major goal and an effective tool of systems biology in studying mechanisms that orchestrate the activities of gene products in cells. Biological networks are context specific and dynamic in…

Molecular Networks · Quantitative Biology 2014-02-20 Ye Tian , Bai Zhang , Eric P. Hoffman , Robert Clarke , Zhen Zhang , Ie-Ming Shih , Jianhua Xuan , David M. Herrington , Yue Wang

We consider the problem of computing matrix polynomials $p(X)$, where $X$ is a large dense matrix, with as few matrix-matrix multiplications as possible. More precisely, let $\Pi_{2^{m}}^*$ represent the set of polynomials computable with…

Numerical Analysis · Mathematics 2025-08-14 Elias Jarlebring , Gustaf Lorentzon

Graphs and various graph-like combinatorial structures, such as preorders and hypergraphs, are ubiquitous in programming. This paper focuses on representing graphs in a purely functional programming language like Haskell. There are several…

Programming Languages · Computer Science 2022-02-21 Andrey Mokhov

The framework of algebraically natural proofs was independently introduced in the works of Forbes, Shpilka and Volk (2018), and Grochow, Kumar, Saks and Saraf (2017), to study the efficacy of commonly used techniques for proving lower…

Computational Complexity · Computer Science 2025-02-04 Prerona Chatterjee , Mrinal Kumar , C Ramya , Ramprasad Saptharishi , Anamay Tengse

We study an inverse design problem for the linear multiple fragmentation equation arising in particle dynamics. Our objective is to reconstruct an unknown initial size distribution that evolves, under a prescribed fragmentation law, into a…

Optimization and Control · Mathematics 2026-02-20 Arijit Das

In a recent paper, I. Selesnick and C.S. Burrus developed a design method for maximally flat FIR low-pass digital filters with reduced group delay. Their approach leads to a system of polynomial equations depending on three integer design…

Numerical Analysis · Mathematics 2025-10-20 John B. Little

Understanding the internal representations learned by neural networks is a cornerstone challenge in the science of machine learning. While there have been significant recent strides in some cases towards understanding how neural networks…

Machine Learning · Computer Science 2024-02-20 Depen Morwani , Benjamin L. Edelman , Costin-Andrei Oncescu , Rosie Zhao , Sham Kakade

The Survivable Network Design problem (SNDP) is a well-studied problem, motivated by the design of networks that are robust to faults under the assumption that any subset of edges up to a specific number can fail. We consider non-uniform…

Data Structures and Algorithms · Computer Science 2024-03-26 Chandra Chekuri , Rhea Jain

We present a new method for solving symbolically zero--dimensional polynomial equation systems in the affine and toric case. The main feature of our method is the use of problem adapted data structures: arithmetic networks and…

alg-geom · Mathematics 2008-02-03 M. Giusti , J. Heintz , J. E. Morais , J. Morgenstern , L. M. Pardo

We consider the geometry associated to the ambiguities of the one-dimensional Fourier phase retrieval problem for vectors in ${\mathbb C}^{N+1}$. Our first result states that the space of signals has a finite covering (which we call the…

Functional Analysis · Mathematics 2019-09-24 Dan Edidin

We propose a new family of combinatorial inference problems for graphical models. Unlike classical statistical inference where the main interest is point estimation or parameter testing, combinatorial inference aims at testing the global…

Statistics Theory · Mathematics 2018-02-14 Matey Neykov , Junwei Lu , Han Liu

The Wiener index of a network, introduced by the chemist Harry Wiener, is the sum of distances between all pairs of nodes in the network. This index, originally used in chemical graph representations of the non-hydrogen atoms of a molecule,…

Computational Geometry · Computer Science 2023-03-03 A. Karim Abu-Affash , Paz Carmi , Ori Luwisch , Joseph S. B. Mitchell