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We consider robust submodular maximization problems (RSMs), where given a set of $m$ monotone submodular objective functions, the robustness is with respect to the worst-case (scaled) objective function. The model we consider generalizes…

Optimization and Control · Mathematics 2023-06-12 Hsin-Yi Huang , Hao-Hsiang Wu , Simge Kucukyavuz

We present a method for the synthesis of polynomial lasso programs. These programs consist of a program stem, a set of transitions, and an exit condition, all in the form of algebraic assertions (conjunctions of polynomial equalities).…

Logic in Computer Science · Computer Science 2013-11-19 Jan Leike , Ashish Tiwari

We analyse the complexity of the satisfiability problem ssmSAT for State Space Models (SSM), which asks whether an input sequence can lead the model to an accepting configuration. We find that ssmSAT is undecidable in general, reflecting…

Logic in Computer Science · Computer Science 2025-08-26 Eric Alsmann , Martin Lange

We consider the computation of the matrix logarithm by using numerical quadrature. The efficiency of numerical quadrature depends on the integrand and the choice of quadrature formula. The Gauss--Legendre quadrature has been conventionally…

Numerical Analysis · Mathematics 2019-09-09 Fuminori Tatsuoka , Tomohiro Sogabe , Yuto Miyatake , Shao-Liang Zhang

Many fundamental NP-hard problems can be formulated as integer linear programs (ILPs). A famous algorithm by Lenstra solves ILPs in time that is exponential only in the dimension of the program, and polynomial in the size of the ILP. That…

Data Structures and Algorithms · Computer Science 2017-11-10 Dušan Knop , Martin Koutecký , Matthias Mnich

Generative large language models (LLMs) with instruct training such as GPT-4 can follow human-provided instruction prompts and generate human-like responses to these prompts. Apart from natural language responses, they have also been found…

Artificial Intelligence · Computer Science 2023-09-29 Sumit Kumar Jha , Susmit Jha , Patrick Lincoln , Nathaniel D. Bastian , Alvaro Velasquez , Rickard Ewetz , Sandeep Neema

We consider here Linear Temporal Logic (LTL) formulas interpreted over \emph{finite} traces. We denote this logic by LTLf. The existing approach for LTLf satisfiability checking is based on a reduction to standard LTL satisfiability…

Logic in Computer Science · Computer Science 2014-03-10 Jianwen Li , Lijun Zhang , Geguang Pu , Moshe Y. Vardi , Jifeng He

Emulators that can bypass computationally expensive scientific calculations with high accuracy and speed can enable new studies of fundamental science as well as more potential applications. In this work we discuss solving a system of…

Nuclear Theory · Physics 2022-07-06 Avik Sarkar , Dean Lee

In order to verify programs or hybrid systems, one often needs to prove that certain formulas are unsatisfiable. In this paper, we consider conjunctions of polynomial inequalities over the reals. Classical algorithms for deciding these not…

Numerical Analysis · Mathematics 2009-02-02 David Monniaux

Let us extend the pair of operations (max,+) over real numbers to matrices in the same way as in conventional linear algebra. We study integer images of max-plus linear mappings. The question whether Ax (in the max-plus algebra) is an…

Commutative Algebra · Mathematics 2017-09-27 Peter Butkovic

Large Language Models (LLMs) have exhibited remarkable capabilities in many complex tasks including mathematical reasoning. However, traditional approaches heavily rely on ensuring self-consistency within single prompting method, which…

Computation and Language · Computer Science 2024-10-15 Gisang Lee , Sangwoo Park , Junyoung Park , Andrew Chung , Sieun Park , Yoonah Park , Byungju Kim , Min-gyu Cho

This paper argues that the method of least squares has significant unfulfilled potential in modern machine learning, far beyond merely being a tool for fitting linear models. To release its potential, we derive custom gradients that…

Machine Learning · Computer Science 2025-10-23 Hrittik Roy , Søren Hauberg , Nicholas Krämer

Large Language Models (LLMs) are increasingly used as proxy students in the development of Intelligent Tutoring Systems (ITSs) and in piloting test questions. However, to what extent these proxy students accurately emulate the behavior and…

Computation and Language · Computer Science 2025-07-14 KV Aditya Srivatsa , Kaushal Kumar Maurya , Ekaterina Kochmar

Matrix functions are a central topic of linear algebra, and problems requiring their numerical approximation appear increasingly often in scientific computing. We review various limited-memory methods for the approximation of the action of…

Numerical Analysis · Mathematics 2020-10-26 Stefan Güttel , Daniel Kressner , Kathryn Lund

The Maximum Satisfiability problem (MaxSAT) is a major optimization challenge with numerous practical applications. In recent MaxSAT evaluations, most MaxSAT solvers have incorporated an Integer Linear Programming (ILP) solver into their…

Artificial Intelligence · Computer Science 2026-01-27 Jialu Zhang , Chu-Min Li , Sami Cherif , Shuolin Li , Zhifei Zheng

Computers calculate transcendental functions by approximating them through the composition of a few limited-precision instructions. For example, an exponential can be calculated with a Taylor series. These approximation methods were…

Neural and Evolutionary Computing · Computer Science 2023-12-15 Esteban Real , Yao Chen , Mirko Rossini , Connal de Souza , Manav Garg , Akhil Verghese , Moritz Firsching , Quoc V. Le , Ekin Dogus Cubuk , David H. Park

We introduce Parametric Linear Dynamic Logic (PLDL), which extends Linear Dynamic Logic (LDL) by temporal operators equipped with parameters that bound their scope. LDL itself was proposed as an extension of Linear Temporal Logic (LTL) that…

Logic in Computer Science · Computer Science 2015-12-08 Peter Faymonville , Martin Zimmermann

In this paper, we present a new, graph-based modeling approach and a polynomial-sized linear programming (LP) formulation of the Boolean satisfiability problem (SAT). The approach is illustrated with a numerical example.

Discrete Mathematics · Computer Science 2016-10-21 Moustapha Diaby

This paper deals with exploiting symmetry for solving linear and integer programming problems. Basic properties of linear representations of finite groups can be used to reduce symmetric linear programming to solving linear programs of…

Optimization and Control · Mathematics 2015-07-31 Richard Bödi , Katrin Herr , Michael Joswig

Optimizing and certifying the positivity of polynomials are fundamental primitives across mathematics and engineering applications, from dynamical systems to operations research. However, solving these problems in practice requires large…

Machine Learning · Computer Science 2023-12-05 Hannah Lawrence , Mitchell Tong Harris
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