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An uniform LP duality is an useful property of conic matrix systems. A consistent linear conic optimization problem yields uniform LP duality if for any linear cost function, for which the primal problem has finite optimal value, the…

Optimization and Control · Mathematics 2023-02-21 Kostyukova O. I. , Tchemisova T. , Dudina O. S

Tensor completion is a core machine learning algorithm used in recommender systems and other domains with missing data. While the matrix case is well-understood, theoretical results for tensor problems are limited, particularly when the…

Machine Learning · Statistics 2023-06-13 Kameron Decker Harris , Oscar López , Angus Read , Yizhe Zhu

A cornerstone of geometric reconstruction, rotation averaging seeks the set of absolute rotations that optimally explains a set of measured relative orientations between them. In spite of being an integral part of bundle adjustment and…

Computer Vision and Pattern Recognition · Computer Science 2023-09-08 Gabriel Moreira , Manuel Marques , João Paulo Costeira

The singular values of a product of $M$ independent Ginibre matrices of size $N\times N$ form a determinantal point process. Near the soft edge, as both $M$ and $N$ go to infinity in such a way that $M/N\to \alpha$, $\alpha>0$, a scaling…

Probability · Mathematics 2021-12-21 Sergey Berezin , Eugene Strahov

Current differentiable renderers provide light transport gradients with respect to arbitrary scene parameters. However, the mere existence of these gradients does not guarantee useful update steps in an optimization. Instead, inverse…

Computer Vision and Pattern Recognition · Computer Science 2023-03-29 Michael Fischer , Tobias Ritschel

The 'exact subgraph' approach was recently introduced as a hierarchical scheme to get increasingly tight semidefinite programming relaxations of several NP-hard graph optimization problems. Solving these relaxations is a computational…

Optimization and Control · Mathematics 2019-08-09 Elisabeth Gaar , Franz Rendl

For a graph \(G\) with no isolated vertices, its Laplacian ratio is defined as \[ \pi(G)=\frac{\operatorname{per}(L(G))}{\prod_{v\in V(G)} d(v)}, \] where \(L(G)\) is the Laplacian matrix of \(G\), \(d(v)\) is the degree of \(v\), and…

Combinatorics · Mathematics 2026-05-15 Priyanshu Pant

We study here sparse recovery problems in the presence of additive noise. We analyze a thresholding version of the CoSaMP algorithm, named Thresholding Greedy Pursuit (TGP). We demonstrate that an appropriate choice of thresholding…

Signal Processing · Electrical Eng. & Systems 2021-03-23 Hai Le , Alexei Novikov

In this paper, a second-order generalized Riemann problem (GRP) solver is developed for a two-layer thin film model. Extending the first-order Godunov approach, the solver is used to construct a temporal-spatial coupled second-order…

Numerical Analysis · Mathematics 2025-05-27 Rahul Barthwal , Christian Rohde , Yue Wang

We develop a general strategy in order to implement (approximate) discrete transparent boundary conditions for finite difference approximations of the two-dimensional transport equation. The computational domain is a rectangle equipped with…

Analysis of PDEs · Mathematics 2019-09-12 Christophe Besse , Jean-François Coulombel , Pascal Noble

The matrix completion problem aims to reconstruct a low-rank matrix based on a revealed set of possibly noisy entries. Prior works consider completing the entire matrix with generalization error guarantees. However, the completion accuracy…

Machine Learning · Computer Science 2023-12-19 Elad Hazan , Adam Tauman Kalai , Varun Kanade , Clara Mohri , Y. Jennifer Sun

The generalized reciprocal distance matrix $RD_{\alpha}(G)$ was defined as $RD_{\alpha}(G)=\alpha RT(G)+(1-\alpha)RD(G),\quad 0\leq \alpha \leq 1.$ Let $\lambda_{1}(RD_{\alpha}(G))\geq \lambda_{2}(RD_{\alpha}(G))\geq \cdots \geq…

Combinatorics · Mathematics 2022-07-13 Hechao Liu , Yufei Huang

We propose a novel hierarchical model for multitask bipartite ranking. The proposed approach combines a matrix-variate Gaussian process with a generative model for task-wise bipartite ranking. In addition, we employ a novel trace…

Machine Learning · Computer Science 2013-02-12 Oluwasanmi Koyejo , Cheng Lee , Joydeep Ghosh

Guruswami and Sinop give a $O(1/\delta)$ approximation guarantee for the non-uniform Sparsest Cut problem by solving $O(r)$-level Lasserre semidefinite constraints, provided that the generalized eigenvalues of the Laplacians of the cost and…

Data Structures and Algorithms · Computer Science 2014-06-30 Amit Deshpande , Rakesh Venkat

We investigate the problem of certifying optimality for sparse generalized linear models (GLMs), where sparsity is enforced through a cardinality constraint. While Branch-and-Bound (BnB) frameworks can certify optimality using perspective…

Optimization and Control · Mathematics 2026-03-03 Jiachang Liu , Andrea Lodi , Soroosh Shafiee

This article develops a duality principle for a class of optimization problems in $\mathbb{R}^n$. The results are obtained based on standard tools of convex analysis and on a well known result of Toland for D.C. optimization. Global…

Optimization and Control · Mathematics 2019-04-02 Fabio Botelho

This paper studies dynamic stochastic optimization problems parametrized by a random variable. Such problems arise in many applications in operations research and mathematical finance. We give sufficient conditions for the existence of…

Optimization and Control · Mathematics 2011-05-06 Teemu Pennanen , Ari-Pekka Perkkiö

This paper presents tractable reformulations of topology optimization problems of structures subject to frictionless unilateral contact conditions. Specifically, we consider stiffness maximization problems of trusses and continua. Based on…

Optimization and Control · Mathematics 2020-11-17 Yoshihiro Kanno

In this article, we consider the residual regularization path-following method with the trust-region updating strategy for the linear complementarity problem. This time-stepping selection based on the trust-region updating strategy…

Optimization and Control · Mathematics 2023-01-31 Xin-long Luo , Sen Zhang , Hang Xiao

We consider the problem of efficiently solving large-scale linear least squares problems that have one or more linear constraints that must be satisfied exactly. Whilst some classical approaches are theoretically well founded, they can face…

Numerical Analysis · Mathematics 2021-12-24 Jennifer Scott , Miroslav Tuma