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Related papers: GUBS Upper Bound Solver (Extended Abstract)

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This paper investigates the problem of determining a binary-valued function through a sequence of strategically selected queries. The focus is an algorithm called Generalized Binary Search (GBS). GBS is a well-known greedy algorithm for…

Machine Learning · Statistics 2013-06-26 Robert D. Nowak

We present a new approach to automated reasoning about higher-order programs by endowing symbolic execution with a notion of higher-order, symbolic values. Our approach is sound and relatively complete with respect to a first-order solver…

Programming Languages · Computer Science 2016-03-22 Phuc C. Nguyen , Sam Tobin-Hochstadt , David Van Horn

The purpose of this paper is twofold. An immediate practical use of the presented algorithm is its applicability to the parametric solution of underdetermined linear ordinary differential equations (ODEs) with coefficients that are…

Symbolic Computation · Computer Science 2011-08-24 Thomas Wolf

We improve the known upper bound for short exponential sums and increase the range on which a sharp upper bound is known.

Number Theory · Mathematics 2012-01-13 Anne-Maria Ernvall-Hytönen

Gaussian Boson Sampling (GBS) have shown advantages over classical methods for performing some specific sampling tasks. To fully harness the computational power of GBS, there has been great interest in identifying their practical…

Quantum Physics · Physics 2025-02-28 Jørgen Ellegaard Andersen , Shan Shan

In this paper, we propose a hybrid framework to solve large-scale permutation-based combinatorial problems effectively using a high-performance quadratic unconstrained binary optimization (QUBO) solver. To do so, transformations are…

Optimization and Control · Mathematics 2021-07-07 Siong Thye Goh , Sabrish Gopalakrishnan , Jianyuan Bo , Hoong Chuin Lau

This paper shows that the OSGA algorithm -- which uses first-order information to solve convex optimization problems with optimal complexity -- can be used to efficiently solve arbitrary bound-constrained convex optimization problems. This…

Optimization and Control · Mathematics 2015-01-08 Masoud Ahookhosh , Arnold Neumaier

The problem of computing the optimum of a function on a finite set is an important problem in mathematics and computer science. Many combinatorial problems such as MAX-SAT and MAXCUT can be recognized as optimization problems on the…

Optimization and Control · Mathematics 2023-02-07 Jiangting Yang , Ke Ye , Lihong Zhi

This paper develops a new framework for program synthesis, called semantics-guided synthesis (SemGuS), that allows a user to provide both the syntax and the semantics for the constructs in the language. SemGuS accepts a recursively defined…

Programming Languages · Computer Science 2020-11-12 Jinwoo Kim , Qinheping Hu , Loris D'Antoni , Thomas Reps

We consider the problem of solving floating-point constraints obtained from software verification. We present UppSAT --- a new implementation of a systematic approximation refinement framework [ZWR17] as an abstract SMT solver. Provided…

Logic in Computer Science · Computer Science 2017-12-12 Aleksandar Zeljic , Peter Backeman , Christoph M. Wintersteiger , Philipp Ruemmer

The lower and upper bound of any given algorithm is one of the most crucial pieces of information needed when evaluating the computational effectiveness for said algorithm. Here a novel method of Boolean Algebraic Programming for symbolic…

Data Structures and Algorithms · Computer Science 2014-07-14 Daniel McCormack

A sup-interpretation is a tool which provides an upper bound on the size of a value computed by some symbol of a program. Sup-interpretations have shown their interest to deal with the complexity of first order functional programs. For…

Programming Languages · Computer Science 2007-06-18 Jean-Yves Marion , Romain Pechoux

We describe a framework for reformulating and solving optimization problems that generalizes the well-known framework originally introduced by Benders. We discuss details of the application of the procedures to several classes of…

Optimization and Control · Mathematics 2023-07-14 Suresh Bolusani , Ted K. Ralphs

Finite geometry is employed to underpin operators in finite, d, dimensional Hilbert space. The central role of mutual unbiased bases (MUB) states projectors is exhibited. Interrelation among operators in Hilbert space, revealed through…

Quantum Physics · Physics 2011-12-21 M. Revzen

Computer programs, so-called solvers, for solving the well-known Boolean satisfiability problem (Sat) have been improving for decades. Among the reasons, why these solvers are so fast, is the implicit usage of the formula's structural…

Artificial Intelligence · Computer Science 2022-08-25 Markus Hecher

Methods developed for the analysis of non-linear integrable models are used in the harmonic superspace (HS) framework. These methods, when applied to the HS, can lead to extract more information about the meaning of integrability in…

High Energy Physics - Theory · Physics 2009-10-31 M. Hssaini , M. Kessabi , B. Maroufi , M. B. Sedra

Graduated optimization is a global optimization technique that is used to minimize a multimodal nonconvex function by smoothing the objective function with noise and gradually refining the solution. This paper experimentally evaluates the…

Machine Learning · Computer Science 2024-12-17 Naoki Sato , Hideaki Iiduka

The computation of amoebas has been a challenging open problem for the last dozen years. The most natural approach, namely to compute an amoeba via its boundary, has not been practical so far since only a superset of the boundary, the…

Algebraic Geometry · Mathematics 2016-06-14 Franziska Schroeter , Timo de Wolff

Over-approximating the forward reach sets of controlled dynamical systems subject to set-valued uncertainties is a common practice in systems-control engineering for the purpose of performance verification. However, specific algebraic and…

Optimization and Control · Mathematics 2022-02-16 Shadi Haddad , Abhishek Halder

The known a posteriori error analysis of hybrid high-order methods (HHO) treats the stabilization contribution as part of the error and as part of the error estimator for an efficient and reliable error control. This paper circumvents the…

Numerical Analysis · Mathematics 2024-07-03 Fleurianne Bertrand , Carsten Carstensen , Benedikt Gräßle , Ngoc Tien Tran