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We continue the study of counting complexity begun in [Buergisser, Cucker 04] and [Buergisser, Cucker, Lotz 05] by proving upper and lower bounds on the complexity of computing the Hilbert polynomial of a homogeneous ideal. We show that the…

Symbolic Computation · Computer Science 2007-05-23 Peter Buergisser , Martin Lotz

In the computation of a Gr"obner basis using Buchberger's algorithm, a key issue for improving the efficiency is to produce techniques for avoiding as many unnecessary critical pairs as possible. A good solution would be to avoid _all_…

Commutative Algebra · Mathematics 2007-05-23 M. Caboara , M. Kreuzer , L. Robbiano

To integer programming problems, computational algebraic approaches using Grobner bases or standard pairs via the discreteness of toric ideals have been studied in recent years. Although these approaches have not given improved time…

Combinatorics · Mathematics 2007-05-23 Takayuki Ishizeki , Hiroki Nakayama , Hiroshi Imai

It is known that for binary codes one can use Gr\"obner bases to obtain a subset of codewords of minimal support that can be used to determine the second generalized Hamming weight of the code. In this paper we establish conditions on a…

Commutative Algebra · Mathematics 2025-10-14 Hernán de Alba , Cecilia Martínez-Reyes

We compute the nonlinearity of Boolean functions with Groebner basis techniques, providing two algorithms: one over the binary field and the other over the rationals. We also estimate their complexity. Then we show how to improve our…

Information Theory · Computer Science 2014-04-11 E. Bellini , I. Simonetti , M. Sala

We study the computational complexity of the map redistricting problem (gerrymandering). Mathematically, the electoral district designer (gerrymanderer) attempts to partition a weighted graph into $k$ connected components (districts) such…

Computer Science and Game Theory · Computer Science 2024-01-09 Jack Dippel , Max Dupré la Tour , April Niu , Sanjukta Roy , Adrian Vetta

Bridging logical and algorithmic reasoning with modern machine learning techniques is a fundamental challenge with potentially transformative impact. On the algorithmic side, many NP-hard problems can be expressed as integer programs, in…

Machine Learning · Computer Science 2024-12-16 Anselm Paulus , Michal Rolínek , Vít Musil , Brandon Amos , Georg Martius

Given a finite set of closed rational points of affine space over a field, we give a Gr\"obner basis for the lexicographic ordering of the ideal of polynomials which vanish at all given points. Our method is an alternative to the…

Commutative Algebra · Mathematics 2007-05-23 Mathias Lederer

In the theory of divisors on multigraphs, the $r^{th}$ divisorial gonality of a graph is the minimum degree of a rank $r$ divisor on that graph. It was proved by Gijswijt et al. that the first divisorial gonality of a finite graph is…

Combinatorics · Mathematics 2022-08-09 Ralph Morrison , Lucas Tolley

We consider the algorithm by Ferson et al. (Reliable computing 11(3), p. 207-233, 2005) designed for solving the NP-hard problem of computing the maximal sample variance over interval data, motivated by robust statistics (in fact, the…

Optimization and Control · Mathematics 2022-07-28 Miroslav Rada , Michal Černý , Ondřej Sokol

Hilbert schemes of zero-dimensional ideals in a polynomial ring can be covered with suitable affine open subschemes whose construction is achieved using border bases. Moreover, border bases have proved to be an excellent tool for describing…

Commutative Algebra · Mathematics 2008-06-26 Lorenzo Robbiano

We provide a complexity classification of four variants of robust integer programming when the underlying Graver basis is given. We discuss applications to robust multicommodity flows and multidimensional transportation, and describe an…

Optimization and Control · Mathematics 2014-11-04 Shmuel Onn

Sparse linear regression is the well-studied inference problem where one is given a design matrix $\mathbf{A} \in \mathbb{R}^{M\times N}$ and a response vector $\mathbf{b} \in \mathbb{R}^M$, and the goal is to find a solution $\mathbf{x}…

Machine Learning · Computer Science 2022-02-17 Aparna Gupte , Vinod Vaikuntanathan

In the number partitioning problem (NPP) one aims to partition a given set of $N$ real numbers into two subsets with approximately equal sum. The NPP is a well-studied optimization problem and is famous for possessing a…

Statistics Theory · Mathematics 2025-05-28 Rushil Mallarapu , Mark Sellke

The 0/1 knapsack problem is weakly NP-hard in that there exist pseudo-polynomial time algorithms based on dynamic programming that can solve it exactly. There are also the core branch and bound algorithms that can solve large randomly…

Neural and Evolutionary Computing · Computer Science 2019-03-11 Shalin Shah

In this work we solve the problem of robustly learning a high-dimensional Gaussian mixture model with $k$ components from $\epsilon$-corrupted samples up to accuracy $\widetilde{O}(\epsilon)$ in total variation distance for any constant $k$…

Machine Learning · Computer Science 2021-11-16 Allen Liu , Ankur Moitra

The independent set polynomial is important in many areas. For every integer $\Delta\geq 2$, the Shearer threshold is the value $\lambda^*(\Delta)=(\Delta-1)^{\Delta-1}/\Delta^{\Delta}$ . It is known that for $\lambda < -…

Computational Complexity · Computer Science 2022-10-25 Andreas Galanis , Leslie Ann Goldberg , Daniel Stefankovic

We study the design of computationally efficient algorithms with provable guarantees, that are robust to adversarial (test time) perturbations. While there has been an proliferation of recent work on this topic due to its connections to…

Machine Learning · Computer Science 2019-11-13 Pranjal Awasthi , Abhratanu Dutta , Aravindan Vijayaraghavan

Dealing with large numbers of symmetries is often problematic. One solution is to focus on just symmetries that generate the symmetry group. Whilst there are special cases where breaking just the symmetries in a generating set is complete,…

Artificial Intelligence · Computer Science 2009-09-29 George Katsirelos , Nina Narodytska , Toby Walsh

We present an standard constraints generation algorithm to find an explicit set whose robustness is equal to the robustness of the feasible solution set of a combinatorial optimization problem with cost uncertainty. Computational experience…

Optimization and Control · Mathematics 2023-04-11 Alejandro Crema