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quantum machine learning

More information about this series at http://www.springer.com/series/7407

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quantum machine learning

Bob Coecke Ariane Lambert-Mogiliansky (Eds.)

Quantum Interaction

11th International Conference, QI 2018

Nice, France, September 35, 2018

Revised Selected Papers

123

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quantum machine learning

Editors

Ariane Lambert-Mogiliansky

Bob Coecke

University of Oxford

Paris School of Economics

Oxford, UK

Paris, France

ISSN

0302-9743

ISSN 1611-3349 (electronic)

Lecture Notes in Computer Science

 

ISBN

978-3-030-35894-5

ISBN 978-3-030-35895-2 (eBook)

https://doi.org/10.1007/978-3-030-35895-2

LNCS Sublibrary: SL1 Theoretical Computer Science and General Issues

© Springer Nature Switzerland AG 2019

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The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specic statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.

The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional afliations.

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quantum machine learning

Preface

Quantum Interaction (QI) is an emerging interdisciplinary eld of science. It proposes applications of quantum theory to a large variety of domains from psychology, economics, semantic and memory, natural language processing, cognition, information retrieval, biology, and political science. The applications addressed typically operate at a macroscopic scale and could not be considered quantum in a quantum mechanical sense. However, they share key properties with quantum systems. These include non-commutativity of measurement, indeterminacy, non-separability, contextuality, and harmonic oscillations. QI thus refers to the use of the quantum mathematical, conceptual, or probabilistic structures outside of physics. Since its inception in 2007, QI has evolved from nearly exclusively theoretical and conceptual contributions to more applied works including lab experiments.

QI 2018, the 11th International Conference on Quantum Interactions was part of a series of international conferences. This now traditional conference started in 2007 as part of the Association for the Advancement of Articial Intelligence (AAAI) Spring Symposia at Stanford University. For the second time the conference was held in France (QI 2012 was in Paris). The 11th conference took place during September 35, 2018, in Nice. It was hosted by Nice Graduate School of Management at the Sophia Antipolis University.

In this years conference we had many distinguished speakers, and we are happy to have contributions to this volume from two of our keynote speakers. Prof. Michel Bitbol, Directeur de recherche CNRS at Ecole Normale Supérieure, Paris, France, offers a philosophical and historical perspective that unveils deep reasons for a quantum approach in human sciences. Prof. B. P. F. Jacobs, from the Institute for Computing and Information Sciences (ICIS), Correctness Digital Security Group at Radboud University Nijmegen, The Netherlands, provides a review of the questions related to updating in the classical and quantum context and introduces challenging research issues related to probabilistic logic.

The conference had an afliated workshop entitled Workshop on Compositional Approaches in Physics, NLP, and Social Sciences (CAPNS 2018). Its proceedings appeared in ENTCS.

We would like to take the opportunity to thank everybody who made this symposium possible: the Steering Committee, the Program Committee members for their reviewing job, the proceedings and the publicity chairs, those responsible for the website design and management, and all the conference participants and presenters. We are grateful for the support given by the University of Nice Sophia Antipolis.

June 2019

Bob Coecke

 

Ariane Lambert-Mogiliansky

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quantum machine learning

Organization

Program Chairs

Bob Coecke

University of Oxford, UK

Ariane

Paris School of Economics, France

Lambert-Mogiliansky

 

Steering Committee

Peter Bruza

Queensland University of Technology, Australia

Trevor Cohen

University of Texas at Houston, USA

Bob Coecke

University of Oxford, UK

Ariane

Paris School of Economics, France

Lambert-Mogiliansky

 

Dominic Widdows

Grab Technologies Inc., USA

Program Committee

Irina Basieva

LNU, Sweden

Bob Coecke

University of Oxford, UK

Trevor Cohen

University of Texas, Houston, USA

Ehtibar Dzhafarov

Purdue University, USA

Bart Jacobs

Radboud University, The Netherlands

Chris Heunen

The University of Edinburgh, UK

Dominic Horsman

University of Durham, UK

Dimitri Kartsaklis

Apple Inc., UK

Kirsty Kitto

University of Technology, Sydney

Andrei Khrennikov

Linnaeus University, Sweden

Ariane

Paris School of Economics, France

Lambert-Mogiliansky

 

Bill Lawless

Paine College, USA

Martha Lewis

University of Amsterdam, The Netherlands

Dan Marsden

University of Oxford, UK

Simon Perdrix

CNRS, University of Grenoble, France

Emmanuel Pothos

City University London, UK

Quanlong Wang

University of Oxford, UK

Local Committee

 

Sébastien Duchêne

University of Nice Sophia Antipolis, France

Ismaël Rafaï

University of Nice Sophia Antipolis, France

Laurence Gervasoni

University of Nice Sophia Antipolis, France