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In recent years, the interest in interpretable classification models has grown. One of the proposed ways to improve the interpretability of a rule-based classification model is to use sets (unordered collections) of rules, instead of lists…

Machine Learning · Computer Science 2020-03-31 Thiago Zafalon Miranda , Diorge Brognara Sardinha , Ricardo Cerri

Linear-parametric optimization, where multiple objectives are combined into a single objective using linear combinations with parameters as coefficients, has numerous links to other fields in optimization and a wide range of application…

Optimization and Control · Mathematics 2025-01-22 Levin Nemesch , Stefan Ruzika , Clemens Thielen , Alina Wittmann

We develop a systematic way to solve linear equations involving tensors of arbitrary rank. We start off with the case of a rank $3$ tensor, which appears in many applications, and after finding the condition for a unique solution we derive…

Mathematical Physics · Physics 2021-09-21 Damianos Iosifidis

This is the first in a series of papers which deal with the development of novel methods for solving a system of linear algebraic equations with a time complexity lower than existing algorithms. The NxN system of linear equations, Ax = b,…

Optimization and Control · Mathematics 2022-06-16 Vilas Patwardhan

A new algorithm for line clipping against convex polyhedron is given. The suggested algorithm is faster for higher number of facets of the given polyhedron than the traditional Cyrus-Beck's and others algorithms with complexity O(N) . The…

Graphics · Computer Science 2018-01-03 Vaclav Skala

Shapes do not define a linear space. This paper explores the linear structure of deformations as a representation of shapes. This transforms shape optimization to a variant of optimal control. The numerical challenges of this point of view…

Optimization and Control · Mathematics 2022-03-15 Stephan Schmidt , Volker H. Schulz

We explore contemporary, data-driven techniques for solving math word problems over recent large-scale datasets. We show that well-tuned neural equation classifiers can outperform more sophisticated models such as sequence to sequence and…

Artificial Intelligence · Computer Science 2018-05-01 Benjamin Robaidek , Rik Koncel-Kedziorski , Hannaneh Hajishirzi

Discrete barycenters are the optimal solutions to mass transport problems for a set of discrete measures. Such transport problems arise in many applications of operations research and statistics. The best known algorithms for exact…

Optimization and Control · Mathematics 2019-04-24 Steffen Borgwardt , Stephan Patterson

Linear constraints are the linear counterpart of Haskell's class constraints. Linearly typed parameters allow the programmer to control resources such as file handles and manually managed memory as linear arguments. Indeed, a linear type…

Programming Languages · Computer Science 2026-04-24 Arnaud Spiwack , Csongor Kiss , Jean-Philippe Bernardy , Nicolas Wu , Richard A. Eisenberg

A recently proposed exact algorithm for the maximum independent set problem is analyzed. The typical running time is improved exponentially in some parameter regions compared to simple binary search. The algorithm also overcomes the core…

Disordered Systems and Neural Networks · Physics 2017-08-02 Jun Takahashi , Satoshi Takabe , Koji Hukushima

The existence of multiple solutions to AC optimal power flow (ACOPF) problems has been noted for decades. Existing solvers are generally successful in finding local solutions, which are stationary points but may not be globally optimal. In…

Systems and Control · Electrical Eng. & Systems 2021-02-25 Ling Zhang , Baosen Zhang

In this paper, we bring a complete solution to the Ovals problem, as formulated in [3] and [24].

Functional Analysis · Mathematics 2025-04-22 Yacine Chitour , Jochen Denzler , Frédéric Jean , Emmanuel Trélat

In this paper we introduce Clause Cuts: linear inequalities obtained from clauses that are logically implied by a CNF formula, resembling strengthened no-good cuts. With these cuts, we tighten mixed-integer linear programming (MILP)…

Optimization and Control · Mathematics 2025-09-29 Max Engelhardt , Milan Adhikari , Jonasz Staszek , Alexander Martin

We introduce a convex optimization modeling framework that transforms a convex optimization problem expressed in a form natural and convenient for the user into an equivalent cone program in a way that preserves fast linear transforms in…

Optimization and Control · Mathematics 2015-11-05 Steven Diamond , Stephen Boyd

We show how to reduce the problem of solving members of a certain family of nonlinear differential equations to that of solving some corresponding linear differential equations.

General Mathematics · Mathematics 2023-05-10 Kerry M. Soileau

Given a set of coins arranged in a line, we remove heads-up coins one at a time and flip any adjacent coins after each removal. The coin-removal problem is to determine for which arrangements of coins it is possible to remove all of the…

Combinatorics · Mathematics 2007-05-23 Kennan Shelton , Michael Siler

Constrained optimization problems appear in a wide variety of challenging real-world problems, where constraints often capture the physics of the underlying system. Classic methods for solving these problems rely on iterative algorithms…

Systems and Control · Electrical Eng. & Systems 2023-06-13 Meiyi Li , Soheil Kolouri , Javad Mohammadi

We introduce a new methodology dubbed ``safe peeling'' to accelerate the resolution of L0-regularized least-squares problems via a Branch-and-Bound (BnB) algorithm. Our procedure enables to tighten the convex relaxation considered at each…

Machine Learning · Computer Science 2023-06-07 Théo Guyard , Gilles Monnoyer , Clément Elvira , Cédric Herzet

For a linear complementarity problem, we present a relaxaiton accelerated two-sweep matrix splitting iteration method. The convergence analysis illustrates that the proposed method converges to the exact solution of the linear…

Optimization and Control · Mathematics 2020-12-02 Dongkai Li , Li Wang , Yuying Liu

Streamliner constraints reduce the search space of combinatorial problems by ruling out portions of the solution space. We adapt the StreamLLM approach, which uses Large Language Models (LLMs) to generate streamliners for Constraint…

Logic in Computer Science · Computer Science 2026-04-22 Florentina Voboril , Martin Gebser , Stefan Szeider , Alice Tarzariol