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Related papers: Hard CNF Instances for Ideal Proof Systems

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We present a general framework for good CNF-representations of boolean constraints, to be used for translating decision problems into SAT problems (i.e., deciding satisfiability for conjunctive normal forms). We apply it to the…

Computational Complexity · Computer Science 2014-08-06 Matthew Gwynne , Oliver Kullmann

We design and analyze primal-dual, feasible interior-point algorithms (IPAs) employing full Newton steps to solve convex optimization problems in standard conic form. Unlike most nonsymmetric cone programming methods, the algorithms…

Optimization and Control · Mathematics 2025-02-25 Dávid Papp , Anita Varga

Conformal inference provides a rigorous statistical framework for uncertainty quantification in machine learning, enabling well-calibrated prediction sets with precise coverage guarantees for any classification model. However, its reliance…

In the classic Integer Programming (IP) problem, the objective is to decide whether, for a given $m \times n$ matrix $A$ and an $m$-vector $b=(b_1,\dots, b_m)$, there is a non-negative integer $n$-vector $x$ such that $Ax=b$. Solving (IP)…

Data Structures and Algorithms · Computer Science 2018-07-18 Fedor V. Fomin , Fahad Panolan , M. S. Ramanujan , Saket Saurabh

We study probabilistic iterated function systems (IFS), consisting of a finite or infinite number of average-contracting bi-Lipschitz maps on R^d. If our strong open set condition is also satisfied, we show that both upper and lower bounds…

Dynamical Systems · Mathematics 2015-10-06 Andreas Anckar

Training Deep Neural Networks that are robust to norm bounded adversarial attacks remains an elusive problem. While exact and inexact verification-based methods are generally too expensive to train large networks, it was demonstrated that…

Machine Learning · Computer Science 2021-06-15 Salman Alsubaihi , Adel Bibi , Modar Alfadly , Abdullah Hamdi , Bernard Ghanem

Our contribution in this paper is two folded. We consider first the case of linear programming with real coefficients and give a method which allows the computation of a new upper bound on the distance from the origin to a feasible point.…

Optimization and Control · Mathematics 2020-10-30 Beniamin Costandin , Marius Costandin , Petru Dobra

Assumption-based argumentation (ABA) is a central structured argumentation formalism. As shown recently, answer set programming (ASP) enables efficiently solving NP-hard reasoning tasks of ABA in practice, in particular in the commonly…

Artificial Intelligence · Computer Science 2021-08-10 Tuomo Lehtonen , Johannes P. Wallner , Matti Järvisalo

We present an efficient technique, which allows to train classification networks which are verifiably robust against norm-bounded adversarial attacks. This framework is built upon the work of Gowal et al., who applies the interval…

Machine Learning · Computer Science 2019-07-04 Paweł Morawiecki , Przemysław Spurek , Marek Śmieja , Jacek Tabor

We study the robust interpolation problem of arbitrary data distributions supported on a bounded space and propose a two-fold law of robustness. Robust interpolation refers to the problem of interpolating $n$ noisy training data points in…

Machine Learning · Computer Science 2023-06-02 Yihan Wu , Heng Huang , Hongyang Zhang

This paper is concerned with the exact solution of mixed-integer programs (MIPs) over the rational numbers, i.e., without any roundoff errors and error tolerances. Here, one computational bottleneck that should be avoided whenever possible…

Optimization and Control · Mathematics 2023-11-08 Leon Eifler , Ambros Gleixner

We define a novel notion of ``non-backtracking'' matrix associated to any symmetric matrix, and we prove a ``Ihara-Bass'' type formula for it. We use this theory to prove new results on polynomial-time strong refutations of random…

Computational Complexity · Computer Science 2023-05-16 Tommaso d'Orsi , Luca Trevisan

This paper first analyzes the resolution complexity of two random CSP models (i.e. Model RB/RD) for which we can establish the existence of phase transitions and identify the threshold points exactly. By encoding CSPs into CNF formulas, it…

Computational Complexity · Computer Science 2007-05-23 Ke Xu , Wei Li

In recent years, we have seen several approaches to the graph isomorphism problem based on "generic" mathematical programming or algebraic (Gr\"obner basis) techniques. For most of these, lower bounds have been established. In fact, it has…

Computational Complexity · Computer Science 2016-07-18 Christoph Berkholz , Martin Grohe

We present a general method for converting any family of unsatisfiable CNF formulas that is hard for one of the simplest proof systems, tree resolution, into formulas that require large rank in any proof system that manipulates polynomials…

Computational Complexity · Computer Science 2009-12-04 Paul Beame , Trinh Huynh , Toniann Pitassi

We investigate the complexity of explicit construction problems, where the goal is to produce a particular object of size $n$ possessing some pseudorandom property in time polynomial in $n$. We give overwhelming evidence that $\bf{APEPP}$,…

Computational Complexity · Computer Science 2022-02-14 Oliver Korten

The Stabbing Planes proof system was introduced to model the reasoning carried out in practical mixed integer programming solvers. As a proof system, it is powerful enough to simulate Cutting Planes and to refute the Tseitin formulas --…

Computational Complexity · Computer Science 2021-05-24 Noah Fleming , Mika Göös , Russell Impagliazzo , Toniann Pitassi , Robert Robere , Li-Yang Tan , Avi Wigderson

We consider approximation algorithms for covering integer programs of the form min $\langle c, x \rangle $ over $x \in \mathbb{N}^n $ subject to $A x \geq b $ and $x \leq d$; where $A \in \mathbb{R}_{\geq 0}^{m \times n}$, $b \in…

Data Structures and Algorithms · Computer Science 2018-11-20 Chandra Chekuri , Kent Quanrud

Formal theorem proving, a field at the intersection of mathematics and computer science, has seen renewed interest with advancements in large language models (LLMs). This paper introduces SubgoalXL, a novel approach that synergizes…

Machine Learning · Computer Science 2024-08-22 Xueliang Zhao , Lin Zheng , Haige Bo , Changran Hu , Urmish Thakker , Lingpeng Kong

Since their introduction by Atserias, Kolaitis, and Vardi in 2004, proof systems where each line is represented by an ordered binary decision diagram (OBDD) have been intensively studied as they allow to compactly represent Boolean…

Computational Complexity · Computer Science 2026-05-13 Matthäus Micun , Christoph Berkholz
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