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Related papers: Lessons I learned from Richard Stanley

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Following the general strategy proposed by G.Rybnikov, we present a proof of his well-known result, that is, the existence of two arrangements of lines having the same combinatorial type, but non-isomorphic fundamental groups. To do so, the…

Algebraic Geometry · Mathematics 2018-05-04 E. Artal , J. Carmona , J. I. Cogolludo , M. A. Marco

Ubiquitous information access becomes more and more important nowadays and research is aimed at making it adapted to users. Our work consists in applying machine learning techniques in order to bring a solution to some of the problems…

Machine Learning · Computer Science 2014-04-01 Djallel Bouneffouf

In these shorts notes I want to remembermy relationship with GianCarlo Ghirardi, who was my supervisor in my Master Degree in Physics at the University of Trieste and then he became a very deep and close friend. I don't want to describe in…

History and Philosophy of Physics · Physics 2018-08-07 Francesco de Stefano

In one of his papers, the author introduces the class of Farkas-related vectors for which a version of Farkas' lemma over integers is derived. In this paper, two similar classes are introduced and studied.

Combinatorics · Mathematics 2015-08-31 Masood Aryapoor

This thesis opens with an introductory discussion, where the reader is gently led to the world of topological combinatorics, and, where the results of this Habilitationsschrift are portrayed against the backdrop of the broader philosophy of…

Algebraic Topology · Mathematics 2007-05-23 Dmitry N. Kozlov

This paper reviews an experiment in human-computer interaction, where interaction takes place when humans attempt to teach a computer to play a strategy board game. We show that while individually learned models can be shown to improve the…

Artificial Intelligence · Computer Science 2009-11-06 Dimitris Kalles , Ilias Fykouras

We study games in which the set of strategies is multi-dimensional, and new agents might learn various strategic dimensions from different mentors. We introduce a new family of dynamics, the recombinator dynamics, which is characterised by…

Theoretical Economics · Economics 2023-11-14 Srinivas Arigapudi , Omer Edhan , Yuval Heller , Ziv Hellman

Imitation learning algorithms learn a policy from demonstrations of expert behavior. We show that, for deterministic experts, imitation learning can be done by reduction to reinforcement learning with a stationary reward. Our theoretical…

Machine Learning · Statistics 2022-03-16 Kamil Ciosek

This text is based on an invited talk at the Dedekind Symposium at Braunschweig in October 2016. It summarizes views from my recent commented edition of Dedekinds two books on the foundations of mathematics.

History and Overview · Mathematics 2017-01-10 Stefan Müller-Stach

Neural networks are being increasingly applied to control and decision-making for learning-enabled cyber-physical systems (LE-CPSs). They have shown promising performance without requiring the development of complex physical models;…

Systems and Control · Electrical Eng. & Systems 2021-03-10 Yixuan Wang , Chao Huang , Zhilu Wang , Shichao Xu , Zhaoran Wang , Qi Zhu

This is a reflection on the author's experience in teaching logic at the graduate level in a computer science department. The main lesson is that model building and the process of modelling must be placed at the centre stage of logic…

Computers and Society · Computer Science 2015-07-19 Roger Villemaire

Every teacher understands that different students benefit from different activities. Recent advances in data processing allow us to detect and use behavioral variability for adapting to a student. This approach allows us to optimize…

Human-Computer Interaction · Computer Science 2017-03-07 Farah Bouassida , Łukasz Kidziński , Pierre Dillenbourg

A few remarks on integrable dynamical systems inspired by discussions with Jurgen Moser and by his work.

Dynamical Systems · Mathematics 2009-11-13 A. P. Veselov

The kind of help a student receives during a task has been shown to play a significant role in their learning process. We designed an interaction scenario with a robotic tutor, in real-life settings based on an inquiry-based learning task.…

Human-Computer Interaction · Computer Science 2018-06-21 Maria Blancas-Muñoz , Vasiliki Vouloutsi , Riccardo Zucca , Anna Mura , Paul F. M. J. Verschure

In the seminal work of Stanley, several conjectures were made on the structure of Littlewood-Richardson coefficients for the multiplication of Jack symmetric functions. Motivated by recent results of Alexandersson and the present author, we…

Combinatorics · Mathematics 2025-07-22 Ryan Mickler

Cooperation between self-interested individuals is a widespread phenomenon in the natural world, but remains elusive in interactions between artificially intelligent agents. Instead, naive reinforcement learning algorithms typically…

Multiagent Systems · Computer Science 2025-01-16 John L. Zhou , Weizhe Hong , Jonathan C. Kao

We study a multiagent learning problem where agents can either learn via repeated interactions, or can follow the advice of a mediator who suggests possible actions to take. We present an algorithmthat each agent can use so that, with high…

Computer Science and Game Theory · Computer Science 2012-06-18 Greg Hines , Kate Larson

This is a former PhD student's take on his teacher's scientific philosophy. I describe a set of 'principles' that I believe are conducive to good applied mathematics, and that I have learnt myself from observing Hans van Duijn in action.

History and Overview · Mathematics 2012-04-25 Mark A. Peletier

In a seminal paper Richard Stanley derived Pieri rules for the Jack symmetric function basis. These rules were extended by Macdonald to his now famous symmetric function basis. The original form of these rules had a forbidding complexity…

Combinatorics · Mathematics 2014-07-31 A. M. Garsia , J. Haglund , G. Xin , M. Zabrocki

This article reviews recent advances in multi-agent reinforcement learning algorithms for large-scale control systems and communication networks, which learn to communicate and cooperate. We provide an overview of this emerging field, with…

Machine Learning · Computer Science 2020-06-24 Donghwan Lee , Niao He , Parameswaran Kamalaruban , Volkan Cevher