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We consider the problem of evaluation of the weight enumerator of a binary linear code. We show that the exact evaluation is hard for polynomial hierarchy. More exactly, if WE is an oracle answering the solution of the evaluation problem…

Computational Complexity · Computer Science 2007-05-23 M. N. Vyalyi

The computation of Gr\"obner bases is an established hard problem. By contrast with many other problems, however, there has been little investigation of whether this hardness is robust. In this paper, we frame and present results on the…

Symbolic Computation · Computer Science 2018-07-18 Gwen Spencer , David Rolnick

In this paper, we study the hardness of decoding a random code endowed with the cover metric. As the cover metric lies in between the Hamming and rank metric, it presents itself as a promising candidate for code-based cryptography. We give…

Information Theory · Computer Science 2022-05-26 Sebastian Bitzer , Julian Renner , Antonia Wachter-Zeh , Violetta Weger

This paper develops upper and lower bounds for the probability of Boolean functions by treating multiple occurrences of variables as independent and assigning them new individual probabilities. We call this approach dissociation and give an…

Artificial Intelligence · Computer Science 2015-06-30 Wolfgang Gatterbauer , Dan Suciu

We prove that there is no fpt-algorithm that can approximate the dominating set problem with any constant ratio, unless FPT= W[1]. Our hardness reduction is built on the second author's recent W[1]-hardness proof of the biclique problem.…

Computational Complexity · Computer Science 2015-11-17 Yijia Chen , Bingkai Lin

Motivated by a problem in computational complexity, we consider the behavior of rank functions for tensors and polynomial maps under random coordinate restrictions. We show that, for a broad class of rank functions called natural rank…

Combinatorics · Mathematics 2024-11-06 Jop Briët , Davi Castro-Silva

We show that for any given norm ball or proper cone, weak membership in its dual ball or dual cone is polynomial-time reducible to weak membership in the given ball or cone. A consequence is that the weak membership or membership problem…

Optimization and Control · Mathematics 2016-07-26 Shmuel Friedland , Lek-Heng Lim

We first show a simple but striking result in bilevel optimization: unconstrained $C^\infty$ smooth bilevel programming is as hard as general extended-real-valued lower semicontinuous minimization. We then proceed to a worst-case analysis…

Computational Complexity · Computer Science 2025-01-29 Jérôme Bolte , Quoc-Tung Le , Edouard Pauwels , Samuel Vaiter

We consider the symmetric Toeplitz matrix completion problem, whose matrix under consideration possesses specific row and column structures. This problem, which has wide application in diverse areas, is well-known to be computationally…

Optimization and Control · Mathematics 2024-03-15 Xihong Yan , Jiahao Guo , Yi Xu

Boolean matrix factorization and Boolean matrix completion from noisy observations are desirable unsupervised data-analysis methods due to their interpretability, but hard to perform due to their NP-hardness. We treat these problems as…

Statistics Theory · Mathematics 2016-02-08 Siamak Ravanbakhsh , Barnabas Poczos , Russell Greiner

The log-rank conjecture in communication complexity suggests that the deterministic communication complexity of any Boolean rank-r function is bounded by polylog(r). Recently, major progress was made by Lovett who proved that the…

Computational Complexity · Computer Science 2014-09-24 Thomas Rothvoss

For bivariate polynomials of degree $n\le 5$ we give fast numerical constructions of determinantal representations with $n\times n$ matrices. Unlike some other available constructions, our approach returns matrices of the smallest possible…

Numerical Analysis · Mathematics 2023-09-18 Anita Buckley , Bor Plestenjak

This paper presents a novel and straight formulation, and gives a complete insight towards the understanding of the complexity of the problems of the so called NP-Class. In particular, this paper focuses in the Searching of the Optimal…

Computational Complexity · Computer Science 2010-06-14 Carlos Barron-Romero

We show that under some widely believed assumptions, there are no higher-order algorithms for basic tasks in computational mathematics such as: Computing integrals with neural network integrands, computing solutions of a Poisson equation…

Numerical Analysis · Mathematics 2025-05-26 Michael Feischl , Fabian Zehetgruber

We answer the following question posed by Lechuga: Given a simply-connected space $X$ with both $H_*(X,\qq)$ and $\pi_*(X)\otimes \qq$ being finite-dimensional, what is the computational complexity of an algorithm computing the cup-length…

Algebraic Topology · Mathematics 2011-12-06 Manuel Amann

In connection with machine arithmetic, we are interested in systems of constraints of the form x + k \leq y + k'. Over integers, the satisfiability problem for such systems is polynomial time. The problem becomes NP complete if we restrict…

Computational Complexity · Computer Science 2008-11-07 Nikolaj Bjørner , Andreas Blass , Yuri Gurevich , Madan Musuvathi

This article presents a technique for proving problems hard for classes of the polynomial hierarchy or for PSPACE. The rationale of this technique is that some problem restrictions are able to simulate existential or universal quantifiers.…

Artificial Intelligence · Computer Science 2007-08-31 Paolo Liberatore

Let $p$ be a prime. Given a polynomial in $\F_{p^m}[x]$ of degree $d$ over the finite field $\F_{p^m}$, one can view it as a map from $\F_{p^m}$ to $\F_{p^m}$, and examine the image of this map, also known as the value set. In this paper,…

Number Theory · Mathematics 2011-11-07 Qi Cheng , Joshua E. Hill , Daqing Wan

Ranking data arises in a wide variety of application areas but remains difficult to model, learn from, and predict. Datasets often exhibit multimodality, intransitivity, or incomplete rankings---particularly when generated by humans---yet…

Machine Learning · Computer Science 2019-01-29 Stephen Ragain , Johan Ugander

The log-determinant of a kernel matrix appears in a variety of machine learning problems, ranging from determinantal point processes and generalized Markov random fields, through to the training of Gaussian processes. Exact calculation of…

Machine Learning · Statistics 2017-04-06 Jack Fitzsimons , Kurt Cutajar , Michael Osborne , Stephen Roberts , Maurizio Filippone
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