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Deterministic finite automata are one of the simplest and most practical models of computation studied in automata theory. Their conceptual extension is the non-deterministic finite automata which also have plenty of applications. In this…

Data Structures and Algorithms · Computer Science 2019-07-24 Sankardeep Chakraborty , Roberto Grossi , Kunihiko Sadakane , Srinivasa Rao Satti

Matrix completion is widely used in machine learning, engineering control, image processing, and recommendation systems. Currently, a popular algorithm for matrix completion is Singular Value Threshold (SVT). In this algorithm, the singular…

Information Retrieval · Computer Science 2019-12-05 Meng Qiao , Zheng Shan , Fudong Liu , Wenjie Sun

A decision tree looks like a simple directed acyclic computational graph, where only the leaf nodes specify the output values and the non-terminals specify their tests or split conditions. From the numerical perspective, we express decision…

Machine Learning · Computer Science 2024-11-07 Jinxiong Zhang

Barvinok introduced the symmetrized determinant ($\sdet$) as a \emph{non-commutative} analogue of the determinant. Intuitively, given a square matrix over an associative algebra, we can obtain the symmetrized determinant by averaging over…

Computational Complexity · Computer Science 2026-05-01 Sanyam Agarwal , Markus Bläser , Mridul Gupta

Characterizing simultaneously diagonalizable (SD) matrices has been receiving considerable attention in the recent decades due to its wide applications and its role in matrix analysis. However, the notion of SD matrices is arguably still…

Numerical Analysis · Mathematics 2022-05-27 Wentao Ding , Jianze Li , Shuzhong Zhang

Current architectures are now equipped with matrix computation units designed to enhance AI and high-performance computing applications. Within these architectures, two fundamental instruction types are matrix multiplication and vector…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-03-04 Wenxuan Zhao , Liang Yuan , Baicheng Yan , Penghao Ma , Yunquan Zhang , Long Wang , Zhe Wang

The max-cut problem is a classical graph theory problem which is NP-complete. The best polynomial time approximation scheme relies on \emph{semidefinite programming} (SDP). We study the conditions under which graphs of certain classes have…

Optimization and Control · Mathematics 2021-09-07 Daniel Hong , Hyunwoo Lee , Alex Wei

Iterative majorize-minimize (MM) (also called optimization transfer) algorithms solve challenging numerical optimization problems by solving a series of "easier" optimization problems that are constructed to guarantee monotonic descent of…

Computation · Statistics 2015-10-23 Madison G. McGaffin , Jeffrey A. Fessler

An algorithm for matrix factorization of polynomials was proposed in \cite{fomatati2022tensor} and it was shown that this algorithm produces better results than the standard method for factoring polynomials on the class of summand-reducible…

Category Theory · Mathematics 2023-04-27 Yves Fomatati

We have recently presented a method to solve an overdetermined linear system of equations with multiple right hand side vectors, where the unknown matrix is to be symmetric and positive definite. The coefficient and the right hand side…

Optimization and Control · Mathematics 2014-09-19 Negin Bagherpour , Nezam Mahdavi-Amiri

We deploy algebraic complexity theoretic techniques for constructing symmetric determinantal representations of for00504925mulas and weakly skew circuits. Our representations produce matrices of much smaller dimensions than those given in…

Computational Complexity · Computer Science 2012-10-24 Bruno Grenet , Erich Kaltofen , Pascal Koiran , Natacha Portier

Given a symmetric D*D matrix M over {0,1,*}, a list M-partition of a graph G is a partition of G's vertices into D parts associated with the rows of M. The part of each vertex is chosen from a given list so that no edge of G maps to a 0 in…

Computational Complexity · Computer Science 2015-04-20 Andreas Göbel , Leslie Ann Goldberg , Colin McQuillan , David Richerby , Tomoyuki Yamakami

Many nonconvex problems in robotics can be relaxed into convex formulations via Semi-Definite Programming (SDP) that can be solved to global optimality. The practical quality of these solutions, however, critically depends on rounding them…

Robotics · Computer Science 2025-10-02 Liangting Wu , Roberto Tron

The Chance-Constrained Parallel Machine Scheduling Problem (CC-PMSP) assigns jobs with uncertain processing times to machines, ensuring that each machine's availability constraints are met with a certain probability. We present a…

Optimization and Control · Mathematics 2025-04-30 Nicolás Casassus , Margarita Castro , Gustavo Angulo

The Sentential Decision Diagram (SDD) is a tractable representation of Boolean functions that subsumes the famous Ordered Binary Decision Diagram (OBDD) as a strict subset. SDDs are attracting much attention because they are more succinct…

Data Structures and Algorithms · Computer Science 2020-04-07 Kengo Nakamura , Shuhei Denzumi , Masaaki Nishino

This paper is concerned with solving some structured multi-linear systems, which are called tensor absolute value equations. This kind of absolute value equations is closely related to tensor complementarity problems and is a generalization…

Numerical Analysis · Mathematics 2017-05-19 Shouqiang Du , Liping Zhang , Chiyu Chen , Liqun Qi

Maximum bipartite matching is a fundamental algorithmic problem which can be solved in polynomial time. We consider a natural variant in which there is a separation constraint: the vertices on one side lie on a path or a grid, and two…

Data Structures and Algorithms · Computer Science 2023-03-20 Pasin Manurangsi , Erel Segal-Halevi , Warut Suksompong

Motivated by a certain molecular reconstruction methodology in cryo-electron microscopy, we consider the problem of solving a linear system with two unknown orthogonal matrices, which is a generalization of the well-known orthogonal…

Optimization and Control · Mathematics 2017-03-07 Teng Zhang , Amit Singer

A major difficulty of solving continuous POMDPs is to infer the multi-modal distribution of the unobserved true states and to make the planning algorithm dependent on the perceived uncertainty. We cast POMDP filtering and planning problems…

Machine Learning · Computer Science 2020-05-08 Yunbo Wang , Bo Liu , Jiajun Wu , Yuke Zhu , Simon S. Du , Li Fei-Fei , Joshua B. Tenenbaum

We present a matrix-theoretic approach for studying and enumerating finite posets through their incidence representations, referred to as poset matrices. Naturally labelled posets are encoded as Boolean lower triangular matrices, allowing a…

Combinatorics · Mathematics 2026-02-05 Gi-Sang Cheon , Hong Joon Choi , Gukwon Kwon , Hojoon Lee , Yaling Wang
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