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The number of possible methods of generalizing binary classification to multi-class classification increases exponentially with the number of class labels. Often, the best method of doing so will be highly problem dependent. Here we present…

Machine Learning · Statistics 2014-05-20 Peter Mills

This text provides an introduction to distributed local algorithms -- an area at the intersection of theoretical computer science and discrete mathematics. We collect recent results in the area and demonstrate how they lead to a clean…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-11-22 Václav Rozhoň

Contribution: We demonstrate that it is feasible to include field specific problems in introductory mathematics courses to motivate engineering students. This is done in a way that still allows large parts of the course to be common to all…

History and Overview · Mathematics 2023-02-14 René Bødker Christensen , Bettina Dahl , Lisbeth Fajstrup

Number partitioning is one of the classical NP-hard problems of combinatorial optimization. It has applications in areas like public key encryption and task scheduling. The random version of number partitioning has an "easy-hard" phase…

Disordered Systems and Neural Networks · Physics 2007-05-23 Stephan Mertens

The purpose of this note is to extend the divergences analyzed in a previous work by application of the Deformed Logarithm in its most general form. In a study on entropic divergences, we have analyzed the different forms of the deformed…

General Mathematics · Mathematics 2023-04-05 Henri Lantéri

A classification algorithm, called the Linear Centralization Classifier (LCC), is introduced. The algorithm seeks to find a transformation that best maps instances from the feature space to a space where they concentrate towards the center…

Machine Learning · Computer Science 2017-12-25 Mohammad Reza Bonyadi , Viktor Vegh , David C. Reutens

This article presents a strongly polynomial-time algorithm for the general linear programming problem. This algorithm is an implicit reduction procedure that works as follows. Primal and dual problems are combined into a special system of…

Optimization and Control · Mathematics 2026-03-24 Samuel Awoniyi

An important endeavor in computer science is to understand the expressive power of logical formalisms over discrete structures, such as words. Naturally, "understanding" is not a mathematical notion. This investigation requires therefore a…

Logic in Computer Science · Computer Science 2023-06-22 Thomas Place , Marc Zeitoun

Bilevel programming problems frequently arise in real-world applications across various fields, including transportation, economics, energy markets and healthcare. These problems have been proven to be NP-hard even in the simplest form with…

Optimization and Control · Mathematics 2024-09-06 Sina Hajikazemi , Florian Steinke

This short course offers a new perspective on randomized algorithms for matrix computations. It explores the distinct ways in which probability can be used to design algorithms for numerical linear algebra. Each design template is…

Numerical Analysis · Mathematics 2025-09-23 Anastasia Kireeva , Joel A. Tropp

Language transformations are algorithms that take a language specification in input, and return the language specification modified. Language transformations are useful for automatically adding features such as subtyping to programming…

Programming Languages · Computer Science 2021-08-25 Matteo Cimini , Benjamin Mourad

A pedagogical approach of problem-based learning with embedded librarianship in several undergraduate mathematics courses is implemented in this educational research. The students are assigned to work on several projects on various…

History and Overview · Mathematics 2015-04-08 N. Karjanto , M. Kairatbekkyzy , J. Agee

Domain generalization is the problem of assigning labels to an unlabeled data set, given several similar data sets for which labels have been provided. Despite considerable interest in this problem over the last decade, there has been no…

Machine Learning · Statistics 2019-05-28 Aniket Anand Deshmukh , Yunwen Lei , Srinagesh Sharma , Urun Dogan , James W. Cutler , Clayton Scott

Large language models (LLMs) have exhibited impressive competence in various tasks, but their internal mechanisms on mathematical problems are still under-explored. In this paper, we study a fundamental question: how language models encode…

Computation and Language · Computer Science 2024-11-15 Fangwei Zhu , Damai Dai , Zhifang Sui

The often elusive Poincar\'e recurrence can be witnessed in a completely separable system. For such systems, the problem of recurrence reduces to the classic mathematical problem of simultaneous Diophantine approximation of multiple…

Quantum Physics · Physics 2017-09-20 J. M. Zhang , Y. Liu

We study theoretical guarantees for solving linear systems in-context using a linear transformer architecture. For in-domain generalization, we provide neural scaling laws that bound the generalization error in terms of the number of tasks…

Machine Learning · Computer Science 2025-05-27 Frank Cole , Yulong Lu , Wuzhe Xu , Tianhao Zhang

Submodularity is an important concept in integer and combinatorial optimization. A classical submodular set function models the utility of selecting homogenous items from a single ground set, and such selections can be represented by binary…

Optimization and Control · Mathematics 2023-04-06 Simge Küçükyavuz , Qimeng Yu

The main point of this paper is to present a class of equations over integers that one can check if they have a solution by checking a set of inequalities. The prototype of such equations is the equations appearing in the well-known…

Combinatorics · Mathematics 2014-06-18 Masood Aryapoor

We discuss issues of problem formulation for algorithms in real algebraic geometry, focussing on quantifier elimination by cylindrical algebraic decomposition. We recall how the variable ordering used can have a profound effect on both…

Symbolic Computation · Computer Science 2014-06-26 Matthew England

The rapid advancement of Large Language Models (LLMs) has opened new avenues in education. This study examines the use of LLMs in supporting learning in machine learning education; in particular, it focuses on the ability of LLMs to…

Computers and Society · Computer Science 2025-05-27 Smitha Kumar , Michael A. Lones , Manuel Maarek , Hind Zantout