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Poincaré Prize 2015 Alexei Borodin I Am Very Pleased and Honored To
Poincar´ePrize 2015 Alexei Borodin I am very pleased and honored to give the laudatio for Alexei Borodin on his winning the Poincar´ePrize for 2015. Alexei was born and went to school in Donetsk in the Ukraine. In 1992 he was accepted into the famous \mech-mat" Department at Moscow State University, graduating in 1997. At Moscow State he began working with Grigori Olshanski in a marvelous collaboration that continues to this day. He received his PhD under Alexander Kirillov from the University of Pennsylvania in 2001. He was a professor at Caltech from 2003 to 2010, and since then he has been at MIT. I met Borodin about 15 years ago when he was a student at UPenn, and I have been following his career closely since then. His mathematical interests lie in the circle of ideas which connect the representation theory of \big" groups, combinatorics, integrable interacting particle systems and random matrix theory. When I met Borodin I was struck immediately by the freshness of his approach, combined with a professional maturity well beyond his years. He seemed to know and understand everything and I had to keep reminding myself that I was speaking to a young PhD student and not a seasoned colleague of many years standing. Borodin's mathematical and professional maturity was recognized with his very first academic appointment as a full Professor at Caltech in 2003. Following on earlier work of Kerov, Olshanski and Vershik, the key observation of Borodin and Olshanski in the representation theory of \big" groups, such as the infinite symmetric group and the infinite unitary group, is that the characters for the group are naturally associated with stochastic point processes. -
Relational Machine Learning Algorithms
Relational Machine Learning Algorithms by Alireza Samadianzakaria Bachelor of Science, Sharif University of Technology, 2016 Submitted to the Graduate Faculty of the Department of Computer Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Pittsburgh 2021 UNIVERSITY OF PITTSBURGH DEPARTMENT OF COMPUTER SCIENCE This dissertation was presented by Alireza Samadianzakaria It was defended on July 7, 2021 and approved by Dr. Kirk Pruhs, Department of Computer Science, University of Pittsburgh Dr. Panos Chrysanthis, Department of Computer Science, University of Pittsburgh Dr. Adriana Kovashka, Department of Computer Science, University of Pittsburgh Dr. Benjamin Moseley, Tepper School of Business, Carnegie Mellon University ii Copyright c by Alireza Samadianzakaria 2021 iii Relational Machine Learning Algorithms Alireza Samadianzakaria, PhD University of Pittsburgh, 2021 The majority of learning tasks faced by data scientists involve relational data, yet most standard algorithms for standard learning problems are not designed to accept relational data as input. The standard practice to address this issue is to join the relational data to create the type of geometric input that standard learning algorithms expect. Unfortunately, this standard practice has exponential worst-case time and space complexity. This leads us to consider what we call the Relational Learning Question: \Which standard learning algorithms can be efficiently implemented on relational data, and for those that cannot, is there an alternative algorithm that can be efficiently implemented on relational data and that has similar performance guarantees to the standard algorithm?" In this dissertation, we address the relational learning question for the well-known prob- lems of support vector machine (SVM), logistic regression, and k-means clustering. -
Computer Science and Decision Theory Fred S. Roberts1 Abstract 1
Computer Science and Decision Theory Fred S. Roberts1 DIMACS Center, Rutgers University, Piscataway, NJ 08854 USA [email protected] Abstract This paper reviews applications in computer science that decision theorists have addressed for years, discusses the requirements posed by these applications that place great strain on decision theory/social science methods, and explores applications in the social and decision sciences of newer decision-theoretic methods developed with computer science applications in mind. The paper deals with the relation between computer science and decision-theoretic methods of consensus, with the relation between computer science and game theory and decisions, and with \algorithmic decision theory." 1 Introduction Many applications in computer science involve issues and problems that decision theorists have addressed for years, issues of preference, utility, conflict and cooperation, allocation, incentives, consensus, social choice, and measurement. A similar phenomenon is apparent more generally at the interface between computer sci- ence and the social sciences. We have begun to see the use of methods developed by decision theorists/social scientists in a variety of computer science applications. The requirements posed by these computer science applications place great strain on the decision theory/social science methods because of the sheer size of the problems addressed, new contexts in which computational power of agents becomes an issue, limitations on information possessed by players, and the sequential nature of repeated applications. Hence, there is a great need to develop a new generation of methods to satisfy these computer science requirements. In turn, these new methods will provide powerful new tools for social scientists in general and decision theorists in particular. -
James Clerk Maxwell
James Clerk Maxwell JAMES CLERK MAXWELL Perspectives on his Life and Work Edited by raymond flood mark mccartney and andrew whitaker 3 3 Great Clarendon Street, Oxford, OX2 6DP, United Kingdom Oxford University Press is a department of the University of Oxford. It furthers the University’s objective of excellence in research, scholarship, and education by publishing worldwide. Oxford is a registered trade mark of Oxford University Press in the UK and in certain other countries c Oxford University Press 2014 The moral rights of the authors have been asserted First Edition published in 2014 Impression: 1 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, without the prior permission in writing of Oxford University Press, or as expressly permitted by law, by licence or under terms agreed with the appropriate reprographics rights organization. Enquiries concerning reproduction outside the scope of the above should be sent to the Rights Department, Oxford University Press, at the address above You must not circulate this work in any other form and you must impose this same condition on any acquirer Published in the United States of America by Oxford University Press 198 Madison Avenue, New York, NY 10016, United States of America British Library Cataloguing in Publication Data Data available Library of Congress Control Number: 2013942195 ISBN 978–0–19–966437–5 Printed and bound by CPI Group (UK) Ltd, Croydon, CR0 4YY Links to third party websites are provided by Oxford in good faith and for information only. -
The Rainbow and the Worm- Mae-Wan Ho
cover next page > Cover title: The Rainbow and the Worm : The Physics of Organisms author: Ho, Mae-Wan. publisher: World Scientific Publishing Co. isbn10 | asin: 9810234260 print isbn13: 9789810234263 ebook isbn13: 9789810248130 language: English subject Biology--Philosophy, Life (Biology) , Biophysics. publication date: 1998 lcc: QH331H6 1998eb ddc: 570.1 subject: Biology--Philosophy, Life (Biology) , Biophysics. cover next page > < previous page page_i next page > Page i The Rainbow and the Worm The Physics of Organisms 2nd Edition < previous page page_i next page > < previous page page_ii next page > Page ii This page intentionally left blank < previous page page_ii next page > < previous page page_iii next page > Page iii The Rainbow and the Worm The Physics of Organisms 2nd Edition Mae-Wan Ho < previous page page_iii next page > < previous page page_iv next page > Page iv Published by World Scientific Publishing Co. Pte. Ltd. P O Box 128, Farrer Road, Singapore 912805 USA office: Suite 1B, 1060 Main Street, River Edge, NJ 07661 UK office: 57 Shelton Street, Covent Garden, London WC2H 9HE British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library. THE RAINBOW AND THE WORM (2nd Edition) The Physics of Organisms Copyright © 1998 by World Scientific Publishing Co. Pte. Ltd. All rights reserved. This book, or parts thereof, may not be reproduced in any form or by any means, electronic or mechanical, including photocopying, recording or any information storage and retrieval system now known or to be invented, without written permission from the Publisher. For photocopying of material in this volume, please pay a copying fee through the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, USA. -
"Orchestrated Objective Reduction"(Orch OR)
Orchestrated Objective Reduction of Quantum Coherence in Brain Microtubules: The "Orch OR" Model for Consciousness Stuart Hameroff & Roger Penrose, In: Toward a Science of Consciousness - The First Tucson Discussions and Debates, eds. Hameroff, S.R., Kaszniak, A.W. and Scott, A.C., Cambridge, MA: MIT Press, pp. 507-540 (1996) Stuart Hameroff and Roger Penrose ABSTRACT Features of consciousness difficult to understand in terms of conventional neuroscience have evoked application of quantum theory, which describes the fundamental behavior of matter and energy. In this paper we propose that aspects of quantum theory (e.g. quantum coherence) and of a newly proposed physical phenomenon of quantum wave function "self-collapse"(objective reduction: OR -Penrose, 1994) are essential for consciousness, and occur in cytoskeletal microtubules and other structures within each of the brain's neurons. The particular characteristics of microtubules suitable for quantum effects include their crystal-like lattice structure, hollow inner core, organization of cell function and capacity for information processing. We envisage that conformational states of microtubule subunits (tubulins) are coupled to internal quantum events, and cooperatively interact (compute) with other tubulins. We further assume that macroscopic coherent superposition of quantum-coupled tubulin conformational states occurs throughout significant brain volumes and provides the global binding essential to consciousness. We equate the emergence of the microtubule quantum coherence with pre-conscious processing which grows (for up to 500 milliseconds) until the mass-energy difference among the separated states of tubulins reaches a threshold related to quantum gravity. According to the arguments for OR put forth in Penrose (1994), superpositioned states each have their own space-time geometries. -
Clinical Genetics in Britain: Origins and Development
CLINICAL GENETICS IN BRITAIN: ORIGINS AND DEVELOPMENT The transcript of a Witness Seminar held by the Wellcome Trust Centre for the History of Medicine at UCL, London, on 23 September 2008 Edited by P S Harper, L A Reynolds and E M Tansey Volume 39 2010 ©The Trustee of the Wellcome Trust, London, 2010 First published by the Wellcome Trust Centre for the History of Medicine at UCL, 2010 The Wellcome Trust Centre for the History of Medicine at UCL is funded by the Wellcome Trust, which is a registered charity, no. 210183. ISBN 978 085484 127 1 All volumes are freely available online following the links to Publications/Wellcome Witnesses at www.ucl.ac.uk/histmed CONTENTS Illustrations and credits v Abbreviations vii Witness Seminars: Meetings and publications; Acknowledgements E M Tansey and L A Reynolds ix Introduction Sir John Bell xix Transcript Edited by P S Harper, L A Reynolds and E M Tansey 1 Appendix 1 Initiatives supporting clinical genetics, 1983–99 by Professor Rodney Harris 83 Appendix 2 The Association of Genetic Nurses and Counsellors (AGNC) by Professor Heather Skirton 87 References 89 Biographical notes 113 Glossary 133 Index 137 ILLUSTRATIONS AND CREDITS Figure 1 Professor Lionel Penrose, c. 1960. Provided by and reproduced with permission of Professor Shirley Hodgson. 8 Figure 2 Dr Mary Lucas, clinical geneticist at the Galton Laboratory, explains a poster to the University of London’s Chancellor, Princess Anne, October 1981. Provided by and reproduced with permission of Professor Joy Delhanty. 9 Figure 3 (a) The karyotype of a phenotypically normal woman and (b) family pedigree, showing three generations with inherited translocation. -
Dynamics, Equations and Applications Book of Abstracts Session
DYNAMICS, EQUATIONS AND APPLICATIONS BOOK OF ABSTRACTS SESSION D21 AGH University of Science and Technology Kraków, Poland 1620 September 2019 2 Dynamics, Equations and Applications CONTENTS Plenary lectures 7 Artur Avila, GENERIC CONSERVATIVE DYNAMICS . .7 Alessio Figalli, ON THE REGULARITY OF STABLE SOLUTIONS TO SEMI- LINEAR ELLIPTIC PDES . .7 Martin Hairer, RANDOM LOOPS . .8 Stanislav Smirnov, 2D PERCOLATION REVISITED . .8 Shing-Tung Yau, STABILITY AND NONLINEAR PDES IN MIRROR SYMMETRY8 Maciej Zworski, FROM CLASSICAL TO QUANTUM AND BACK . .9 Public lecture 11 Alessio Figalli, FROM OPTIMAL TRANSPORT TO SOAP BUBBLES AND CLOUDS: A PERSONAL JOURNEY . 11 Invited talks of part D2 13 Stefano Bianchini, DIFFERENTIABILITY OF THE FLOW FOR BV VECTOR FIELDS . 13 Yoshikazu Giga, ON THE LARGE TIME BEHAVIOR OF SOLUTIONS TO BIRTH AND SPREAD TYPE EQUATIONS . 14 David Jerison, THE TWO HYPERPLANE CONJECTURE . 14 3 4 Dynamics, Equations and Applications Sergiu Klainerman, ON THE NONLINEAR STABILITY OF BLACK HOLES . 15 Aleksandr Logunov, ZERO SETS OF LAPLACE EIGENFUCNTIONS . 16 Felix Otto, EFFECTIVE BEHAVIOR OF RANDOM MEDIA . 17 Endre Süli, IMPLICITLY CONSTITUTED FLUID FLOW MODELS: ANALYSIS AND APPROXIMATION . 17 András Vasy, GLOBAL ANALYSIS VIA MICROLOCAL TOOLS: FREDHOLM THEORY IN NON-ELLIPTIC SETTINGS . 19 Luis Vega, THE VORTEX FILAMENT EQUATION, THE TALBOT EFFECT, AND NON-CIRCULAR JETS . 20 Enrique Zuazua, POPULATION DYNAMICS AND CONTROL . 20 Talks of session D21 23 Giovanni Bellettini, ON THE RELAXED AREA OF THE GRAPH OF NONS- MOOTH MAPS FROM THE PLANE TO THE PLANE . 23 Sun-Sig Byun, GLOBAL GRADIENT ESTIMATES FOR NONLINEAR ELLIP- TIC PROBLEMS WITH NONSTANDARD GROWTH . 24 Juan Calvo, A BRIEF PERSPECTIVE ON TEMPERED DIFFUSION EQUATIONS 25 Giacomo Canevari, THE SET OF TOPOLOGICAL SINGULARITIES OF VECTOR- VALUED MAPS . -
2010 Integral
Autumn 2010 Volume 5 Massachusetts Institute of Technology 1ntegral n e w s f r o m t h e mathematics d e p a r t m e n t a t m i t The retirement of seven of our illustrious col- leagues this year—Mike Artin, David Ben- Inside ney, Dan Kleitman, Arthur Mattuck, Is Sing- er, Dan Stroock, and Alar Toomre—marks • Faculty news 2–3 a shift to a new generation of faculty, from • Women in math 3 those who entered the field in the Sputnik era to those who never knew life without email • A minority perspective 4 and the Internet. The older generation built • Student news 4–5 the department into the academic power- house it is today—indeed they were the core • Funds for RSI and SPUR 5 of the department, its leadership and most • Retiring faculty and staff 6–7 distinguished members, during my early years at MIT. Now, as they are in the process • Alumni corner 8 of retiring, I look around and see that my con- temporaries are becoming the department’s Dear Friends, older group. Yikes! another year gone by and what a year it Other big changes are in the works. Two of Marina Chen have taken the lead in raising an was. We’re getting older, and younger, cele- our dedicated long-term administrators— endowment for them. Together with those of brating prizes and long careers, remembering Joanne Jonsson and Linda Okun—have Tim Lu ’79 and Peiti Tung ’79, their commit- our past and looking to the future. -
A Decade of Lattice Cryptography
Full text available at: http://dx.doi.org/10.1561/0400000074 A Decade of Lattice Cryptography Chris Peikert Computer Science and Engineering University of Michigan, United States Boston — Delft Full text available at: http://dx.doi.org/10.1561/0400000074 Foundations and Trends R in Theoretical Computer Science Published, sold and distributed by: now Publishers Inc. PO Box 1024 Hanover, MA 02339 United States Tel. +1-781-985-4510 www.nowpublishers.com [email protected] Outside North America: now Publishers Inc. PO Box 179 2600 AD Delft The Netherlands Tel. +31-6-51115274 The preferred citation for this publication is C. Peikert. A Decade of Lattice Cryptography. Foundations and Trends R in Theoretical Computer Science, vol. 10, no. 4, pp. 283–424, 2014. R This Foundations and Trends issue was typeset in LATEX using a class file designed by Neal Parikh. Printed on acid-free paper. ISBN: 978-1-68083-113-9 c 2016 C. Peikert All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, mechanical, photocopying, recording or otherwise, without prior written permission of the publishers. Photocopying. In the USA: This journal is registered at the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923. Authorization to photocopy items for in- ternal or personal use, or the internal or personal use of specific clients, is granted by now Publishers Inc for users registered with the Copyright Clearance Center (CCC). The ‘services’ for users can be found on the internet at: www.copyright.com For those organizations that have been granted a photocopy license, a separate system of payment has been arranged. -
The Best Nurturers in Computer Science Research
The Best Nurturers in Computer Science Research Bharath Kumar M. Y. N. Srikant IISc-CSA-TR-2004-10 http://archive.csa.iisc.ernet.in/TR/2004/10/ Computer Science and Automation Indian Institute of Science, India October 2004 The Best Nurturers in Computer Science Research Bharath Kumar M.∗ Y. N. Srikant† Abstract The paper presents a heuristic for mining nurturers in temporally organized collaboration networks: people who facilitate the growth and success of the young ones. Specifically, this heuristic is applied to the computer science bibliographic data to find the best nurturers in computer science research. The measure of success is parameterized, and the paper demonstrates experiments and results with publication count and citations as success metrics. Rather than just the nurturer’s success, the heuristic captures the influence he has had in the indepen- dent success of the relatively young in the network. These results can hence be a useful resource to graduate students and post-doctoral can- didates. The heuristic is extended to accurately yield ranked nurturers inside a particular time period. Interestingly, there is a recognizable deviation between the rankings of the most successful researchers and the best nurturers, which although is obvious from a social perspective has not been statistically demonstrated. Keywords: Social Network Analysis, Bibliometrics, Temporal Data Mining. 1 Introduction Consider a student Arjun, who has finished his under-graduate degree in Computer Science, and is seeking a PhD degree followed by a successful career in Computer Science research. How does he choose his research advisor? He has the following options with him: 1. Look up the rankings of various universities [1], and apply to any “rea- sonably good” professor in any of the top universities. -
Algebraic Pseudorandom Functions with Improved Efficiency from the Augmented Cascade*
Algebraic Pseudorandom Functions with Improved Efficiency from the Augmented Cascade* DAN BONEH† HART MONTGOMERY‡ ANANTH RAGHUNATHAN§ Department of Computer Science, Stanford University fdabo,hartm,[email protected] September 8, 2020 Abstract We construct an algebraic pseudorandom function (PRF) that is more efficient than the classic Naor- Reingold algebraic PRF. Our PRF is the result of adapting the cascade construction, which is the basis of HMAC, to the algebraic settings. To do so we define an augmented cascade and prove it secure when the underlying PRF satisfies a property called parallel security. We then use the augmented cascade to build new algebraic PRFs. The algebraic structure of our PRF leads to an efficient large-domain Verifiable Random Function (VRF) and a large-domain simulatable VRF. 1 Introduction Pseudorandom functions (PRFs), first defined by Goldreich, Goldwasser, and Micali [GGM86], are a fun- damental building block in cryptography and have numerous applications. They are used for encryption, message integrity, signatures, key derivation, user authentication, and many other cryptographic mecha- nisms. Beyond cryptography, PRFs are used to defend against denial of service attacks [Ber96, CW03] and even to prove lower bounds in learning theory. In a nutshell, a PRF is indistinguishable from a truly random function. We give precise definitions in the next section. The fastest PRFs are built from block ciphers like AES and security is based on ad-hoc inter- active assumptions. In 1996, Naor and Reingold [NR97] presented an elegant PRF whose security can be deduced from the hardness of the Decision Diffie-Hellman problem (DDH) defined in the next section.