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It is well known that the affine matrix rank minimization problem is NP-hard and all known algorithms for exactly solving it are doubly exponential in theory and in practice due to the combinational nature of the rank function. In this…

Optimization and Control · Mathematics 2018-04-24 Angang Cui , Haiyang Li , Jigen Peng , Junxiong Jia

Every semigroup which is a finite disjoint union of copies of the free mono- genic semigroup (natural numbers under addition) has soluble word prob- lem and soluble membership problem. Efficient algorithms are given for both problems.

Group Theory · Mathematics 2016-12-08 Nabilah Abughazalah

Polynomial approximations of functions are widely used in scientific computing. In certain applications, it is often desired to require the polynomial approximation to be non-negative (resp. non-positive), or bounded within a given range,…

Numerical Analysis · Mathematics 2024-11-12 Yuan Chen , Dongbin Xiu , Xiangxiong Zhang

The maximum (or minimum) generalized eigenvalue of symmetric positive semidefinite matrices that depend on optimization variables often appears as objective or constraint functions in structural topology optimization when we consider…

Optimization and Control · Mathematics 2024-05-09 Akatsuki Nishioka , Yoshihiro Kanno

Energies with high-order non-submodular interactions have been shown to be very useful in vision due to their high modeling power. Optimization of such energies, however, is generally NP-hard. A naive approach that works for small problem…

Computer Vision and Pattern Recognition · Computer Science 2013-10-09 Carl Olsson , Johannes Ulen , Yuri Boykov , Vladimir Kolmogorov

We study several variants of decomposing a symmetric matrix into a sum of a low-rank positive semidefinite matrix and a diagonal matrix. Such decompositions have applications in factor analysis and they have been studied for many decades.…

Optimization and Control · Mathematics 2023-10-02 Levent Tunçel , Stephen A. Vavasis , Jingye Xu

Submodular optimization generalizes many classic problems in combinatorial optimization and has recently found a wide range of applications in machine learning (e.g., feature engineering and active learning). For many large-scale…

Data Structures and Algorithms · Computer Science 2023-04-11 Matthew Fahrbach , Vahab Mirrokni , Morteza Zadimoghaddam

Matrix decomposition is ubiquitous and has applications in various fields like speech processing, data mining and image processing to name a few. Under matrix decomposition, nonnegative matrix factorization is used to decompose a…

Optimization and Control · Mathematics 2019-05-14 R. Jyothi , P. Babu , R. Bahl

We study the problem of enumerating answers of Conjunctive Queries ranked according to a given ranking function. Our main contribution is a novel algorithm with small preprocessing time, logarithmic delay, and non-trivial space usage during…

Databases · Computer Science 2025-05-21 Shaleen Deep , Paraschos Koutris

Machine learning algorithms use error function minimization to fit a large set of parameters in a preexisting model. However, error minimization eventually leads to a memorization of the training dataset, losing the ability to generalize to…

Machine Learning · Computer Science 2018-03-16 Fernando Martin-Maroto , Gonzalo G. de Polavieja

In this paper, we focus on applications in machine learning, optimization, and control that call for the resilient selection of a few elements, e.g. features, sensors, or leaders, against a number of adversarial denial-of-service attacks or…

Optimization and Control · Mathematics 2017-11-01 Vasileios Tzoumas , Konstantinos Gatsis , Ali Jadbabaie , George J. Pappas

Alternating minimization heuristics seek to solve a (difficult) global optimization task through iteratively solving a sequence of (much easier) local optimization tasks on different parts (or blocks) of the input parameters. While popular…

Computational Complexity · Computer Science 2020-03-10 Peter Bürgisser , Ankit Garg , Rafael Oliveira , Michael Walter , Avi Wigderson

The verification of reductions, representative subsets of interleavings, simplifies correctness proofs of parameterized concurrent programs. We introduce an expressive class of syntactic reductions, which we call natural reductions. Natural…

Programming Languages · Computer Science 2026-05-14 Constantin Enea , Azadeh Farzan , Dominik Klumpp

Optimization problems often involve vector norms, which has led to extensive research on developing algorithms that can handle objectives beyond the $\ell_p$ norms. Our work introduces the concept of submodular norms, which are a versatile…

Data Structures and Algorithms · Computer Science 2023-10-10 Kalen Patton , Matteo Russo , Sahil Singla

Zimin words are very special finite words which are closely related to the pattern-avoidability problem. This problem consists in testing if an instance of a given pattern with variables occurs in almost all words over any finite alphabet.…

Data Structures and Algorithms · Computer Science 2013-07-08 Radosław Głowinski , Wojciech Rytter

We present a generalization of the notion of an algebra norm relevant to real finite-dimensional unital associative algebras. Among other things, this leads to a novel set of algebra isomorphism invariants, some of which are computationally…

Rings and Algebras · Mathematics 2023-12-12 Fred Greensite

We give an algorithm for testing the extremality of a large class of minimal valid functions for the two-dimensional infinite group problem.

Optimization and Control · Mathematics 2017-01-03 Amitabh Basu , Robert Hildebrand , Matthias Köppe

We combine the language of monoids with the language of preorders so as to refine some fundamental aspects of the classical theory of factorization and prove an abstract factorization theorem with a variety of applications. In particular,…

Rings and Algebras · Mathematics 2022-04-15 Salvatore Tringali

Error: Peer-review process exposed an error in Theorem 1 that, unfourtunately, is not repairable. Idempotent semigroups are always finite. See Green and Rees [1952], Siekmann and Szab\'o [1981] for details Anti-unification is a fundamental…

Logic in Computer Science · Computer Science 2025-03-04 David M. Cerna

The minimization of a nonconvex composite function can model a variety of imaging tasks. A popular class of algorithms for solving such problems are majorization-minimization techniques which iteratively approximate the composite nonconvex…

Optimization and Control · Mathematics 2018-09-05 Jonas Geiping , Michael Moeller
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