English
Related papers

Related papers: Constrained Nonnegative Gram Feasibility is $\exis…

200 papers

The following refinement of the Higman embedding theorem is proved: A finitely generated group $R$ is recursively presented if and only if there exists a quasi-isometric malnormal embedding of $R$ into a finitely presented group $H$ such…

Group Theory · Mathematics 2026-03-05 Francis Wagner

If $G(M)$ denotes the subgraph of a graph $G$ induced by the set of vertices that are covered by some matching $M$ in $G$, then $M$ is an induced or a uniquely restricted matching if $G(M)$ is $1$-regular or if $M$ is the unique perfect…

Combinatorics · Mathematics 2018-12-24 Maximilian Fürst

The standard greedy algorithm has been recently shown to enjoy approximation guarantees for constrained non-submodular nondecreasing set function maximization. While these recent results allow to better characterize the empirical success of…

Social and Information Networks · Computer Science 2019-10-09 Khashayar Gatmiry , Manuel Gomez-Rodriguez

We pose the fine-grained hardness hypothesis that the textbook algorithm for the NFA Acceptance problem is optimal up to subpolynomial factors, even for dense NFAs and fixed alphabets. We show that this barrier appears in many variations…

Computational Complexity · Computer Science 2024-10-09 Karl Bringmann , Allan Grønlund , Marvin Künnemann , Kasper Green Larsen

Ill-posed linear inverse problems appear frequently in various signal processing applications. It can be very useful to have theoretical characterizations that quantify the level of ill-posedness for a given inverse problem and the degree…

Signal Processing · Electrical Eng. & Systems 2023-04-26 Justin P. Haldar

The symmetric Nonnegative Matrix Factorization (NMF), a special but important class of the general NMF, has found numerous applications in data analysis such as various clustering tasks. Unfortunately, designing fast algorithms for the…

Machine Learning · Computer Science 2023-01-26 Xiao Li , Zhihui Zhu , Qiuwei Li , Kai Liu

In this paper, we study the general problem of optimizing a convex function $F(L)$ over the set of $p \times p$ matrices, subject to rank constraints on $L$. However, existing first-order methods for solving such problems either are too…

Machine Learning · Statistics 2017-12-12 Mohammadreza Soltani , Chinmay Hegde

The hierarchical matrix framework partitions matrices into subblocks that are either small or of low numerical rank, enabling linear storage complexity and efficient matrix-vector multiplication. This work focuses on the $H^2$-matrix format…

Numerical Analysis · Mathematics 2026-02-02 Anna Yesypenko , Per-Gunnar Martinsson

We study the complexity of satisfiability problems in probabilistic and causal reasoning. Given random variables $X_1, X_2,\ldots$ over finite domains, the basic terms are probabilities of propositional formulas over atomic events $X_i =…

Computational Complexity · Computer Science 2025-04-29 Markus Bläser , Julian Dörfler , Maciej Liśkiewicz , Benito van der Zander

Optimization problems consist of either maximizing or minimizing an objective function. Instead of looking for a maximum solution (resp. minimum solution), one can find a minimum maximal solution (resp. maximum minimal solution). Such…

Data Structures and Algorithms · Computer Science 2018-11-08 Kaveh Khoshkhah , Mehdi Khosravian Ghadikolaei , Jerome Monnot , Florian Sikora

State minimization of combinatorial filters is a fundamental problem that arises, for example, in building cheap, resource-efficient robots. But exact minimization is known to be NP-hard. This paper conducts a more nuanced analysis of this…

Robotics · Computer Science 2023-11-28 Yulin Zhang , Dylan A. Shell

A Fixed-Parameter Tractable (\FPT) $\rho$-approximation algorithm for a minimization (resp. maximization) parameterized problem $P$ is an FPT algorithm that, given an instance $(x, k)\in P$ computes a solution of cost at most $k \cdot…

Data Structures and Algorithms · Computer Science 2013-08-19 Rajesh Chitnis , MohammadTaghi Hajiaghayi , Guy Kortsarz

We consider the problem of reconstructing a low rank matrix from a subset of its entries and analyze two variants of the so-called Alternating Minimization algorithm, which has been proposed in the past. We establish that when the…

Machine Learning · Statistics 2016-09-21 David Gamarnik , Sidhant Misra

In this paper, we demonstrate that in many NP-complete variants of the stable matching problem, such as the Stable Hypergraph Matching problem, the Stable Multicommodity Flow problem, and the College Admission problem with common quotas, a…

Computer Science and Game Theory · Computer Science 2025-02-11 Gergely Csáji

We initiate a systematic study of the computational complexity of the Constraint Satisfaction Problem (CSP) over finite structures that may contain both relations and operations. We show the close connection between this problem and a…

Logic in Computer Science · Computer Science 2021-12-02 Libor Barto , William DeMeo , Antoine Mottet

Using elementary linear algebra, we develop a technique that leads to solutions of two widely known problems on nonnegative matrices. First, we give a short proof of the result by Vavasis stating that the nonnegative rank of a matrix is…

Combinatorics · Mathematics 2018-01-01 Yaroslav Shitov

We systematically study the computational complexity of a broad class of computational problems in phylogenetic reconstruction. The class contains for example the rooted triple consistency problem, forbidden subtree problems, the quartet…

Computational Complexity · Computer Science 2017-08-15 Manuel Bodirsky , Peter Jonsson , Trung Van Pham

In this paper, we review the problem of matrix completion and expose its intimate relations with algebraic geometry, combinatorics and graph theory. We present the first necessary and sufficient combinatorial conditions for matrices of…

Machine Learning · Computer Science 2012-07-03 Franz Kiraly , Ryota Tomioka

The Nystr\"om method is a popular choice for finding a low-rank approximation to a symmetric positive semi-definite matrix. The method can fail when applied to symmetric indefinite matrices, for which the error can be unboundedly large. In…

Numerical Analysis · Mathematics 2023-10-10 Taejun Park , Yuji Nakatsukasa

Given an $n*n$ sparse symmetric matrix with $m$ nonzero entries, performing Gaussian elimination may turn some zeroes into nonzero values. To maintain the matrix sparse, we would like to minimize the number $k$ of these changes, hence…

Computational Complexity · Computer Science 2016-06-28 Yixin Cao , R. B. Sandeep
‹ Prev 1 8 9 10 Next ›