Expander Flows, Geometric Embeddings and Graph Partitioning
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The Multiplicative Weights Update Method: a Meta-Algorithm and Applications
THEORY OF COMPUTING, Volume 8 (2012), pp. 121–164 www.theoryofcomputing.org RESEARCH SURVEY The Multiplicative Weights Update Method: A Meta-Algorithm and Applications Sanjeev Arora∗ Elad Hazan Satyen Kale Received: July 22, 2008; revised: July 2, 2011; published: May 1, 2012. Abstract: Algorithms in varied fields use the idea of maintaining a distribution over a certain set and use the multiplicative update rule to iteratively change these weights. Their analyses are usually very similar and rely on an exponential potential function. In this survey we present a simple meta-algorithm that unifies many of these disparate algorithms and derives them as simple instantiations of the meta-algorithm. We feel that since this meta-algorithm and its analysis are so simple, and its applications so broad, it should be a standard part of algorithms courses, like “divide and conquer.” ACM Classification: G.1.6 AMS Classification: 68Q25 Key words and phrases: algorithms, game theory, machine learning 1 Introduction The Multiplicative Weights (MW) method is a simple idea which has been repeatedly discovered in fields as diverse as Machine Learning, Optimization, and Game Theory. The setting for this algorithm is the following. A decision maker has a choice of n decisions, and needs to repeatedly make a decision and obtain an associated payoff. The decision maker’s goal, in the long run, is to achieve a total payoff which is comparable to the payoff of that fixed decision that maximizes the total payoff with the benefit of ∗This project was supported by David and Lucile Packard Fellowship and NSF grants MSPA-MCS 0528414 and CCR- 0205594. -
Limits on Efficient Computation in the Physical World
Limits on Efficient Computation in the Physical World by Scott Joel Aaronson Bachelor of Science (Cornell University) 2000 A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Computer Science in the GRADUATE DIVISION of the UNIVERSITY of CALIFORNIA, BERKELEY Committee in charge: Professor Umesh Vazirani, Chair Professor Luca Trevisan Professor K. Birgitta Whaley Fall 2004 The dissertation of Scott Joel Aaronson is approved: Chair Date Date Date University of California, Berkeley Fall 2004 Limits on Efficient Computation in the Physical World Copyright 2004 by Scott Joel Aaronson 1 Abstract Limits on Efficient Computation in the Physical World by Scott Joel Aaronson Doctor of Philosophy in Computer Science University of California, Berkeley Professor Umesh Vazirani, Chair More than a speculative technology, quantum computing seems to challenge our most basic intuitions about how the physical world should behave. In this thesis I show that, while some intuitions from classical computer science must be jettisoned in the light of modern physics, many others emerge nearly unscathed; and I use powerful tools from computational complexity theory to help determine which are which. In the first part of the thesis, I attack the common belief that quantum computing resembles classical exponential parallelism, by showing that quantum computers would face serious limitations on a wider range of problems than was previously known. In partic- ular, any quantum algorithm that solves the collision problem—that of deciding whether a sequence of n integers is one-to-one or two-to-one—must query the sequence Ω n1/5 times. -
Computational Pseudorandomness, the Wormhole Growth Paradox, and Constraints on the Ads/CFT Duality
Computational Pseudorandomness, the Wormhole Growth Paradox, and Constraints on the AdS/CFT Duality Adam Bouland Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, 617 Soda Hall, Berkeley, CA 94720, U.S.A. [email protected] Bill Fefferman Department of Computer Science, University of Chicago, 5730 S Ellis Ave, Chicago, IL 60637, U.S.A. [email protected] Umesh Vazirani Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, 671 Soda Hall, Berkeley, CA 94720, U.S.A. [email protected] Abstract The AdS/CFT correspondence is central to efforts to reconcile gravity and quantum mechanics, a fundamental goal of physics. It posits a duality between a gravitational theory in Anti de Sitter (AdS) space and a quantum mechanical conformal field theory (CFT), embodied in a map known as the AdS/CFT dictionary mapping states to states and operators to operators. This dictionary map is not well understood and has only been computed on special, structured instances. In this work we introduce cryptographic ideas to the study of AdS/CFT, and provide evidence that either the dictionary must be exponentially hard to compute, or else the quantum Extended Church-Turing thesis must be false in quantum gravity. Our argument has its origins in a fundamental paradox in the AdS/CFT correspondence known as the wormhole growth paradox. The paradox is that the CFT is believed to be “scrambling” – i.e. the expectation value of local operators equilibrates in polynomial time – whereas the gravity theory is not, because the interiors of certain black holes known as “wormholes” do not equilibrate and instead their volume grows at a linear rate for at least an exponential amount of time. -
Quantum Computing : a Gentle Introduction / Eleanor Rieffel and Wolfgang Polak
QUANTUM COMPUTING A Gentle Introduction Eleanor Rieffel and Wolfgang Polak The MIT Press Cambridge, Massachusetts London, England ©2011 Massachusetts Institute of Technology All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including photocopying, recording, or information storage and retrieval) without permission in writing from the publisher. For information about special quantity discounts, please email [email protected] This book was set in Syntax and Times Roman by Westchester Book Group. Printed and bound in the United States of America. Library of Congress Cataloging-in-Publication Data Rieffel, Eleanor, 1965– Quantum computing : a gentle introduction / Eleanor Rieffel and Wolfgang Polak. p. cm.—(Scientific and engineering computation) Includes bibliographical references and index. ISBN 978-0-262-01506-6 (hardcover : alk. paper) 1. Quantum computers. 2. Quantum theory. I. Polak, Wolfgang, 1950– II. Title. QA76.889.R54 2011 004.1—dc22 2010022682 10987654321 Contents Preface xi 1 Introduction 1 I QUANTUM BUILDING BLOCKS 7 2 Single-Qubit Quantum Systems 9 2.1 The Quantum Mechanics of Photon Polarization 9 2.1.1 A Simple Experiment 10 2.1.2 A Quantum Explanation 11 2.2 Single Quantum Bits 13 2.3 Single-Qubit Measurement 16 2.4 A Quantum Key Distribution Protocol 18 2.5 The State Space of a Single-Qubit System 21 2.5.1 Relative Phases versus Global Phases 21 2.5.2 Geometric Views of the State Space of a Single Qubit 23 2.5.3 Comments on General Quantum State Spaces -
Adwords in a Panorama
2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS) AdWords in a Panorama Zhiyi Huang Qiankun Zhang Yuhao Zhang Computer Science Computer Science Computer Science The University of Hong Kong The University of Hong Kong The University of Hong Kong Hong Kong, China Hong Kong, China Hong Kong, China [email protected] [email protected] [email protected] Abstract—Three decades ago, Karp, Vazirani, and Vazi- with unit bids and unit budgets. Fifteen years later, rani (STOC 1990) defined the online matching problem Mehta et al. [36] formally formulated it as the AdWords and gave an optimal (1-1/e)-competitive (about 0.632) problem. They introduced an optimal 1− 1 -competitive algorithm. Fifteen years later, Mehta, Saberi, Vazirani, e and Vazirani (FOCS 2005) introduced the first general- algorithm under the small-bid assumption: an adver- ization called AdWords driven by online advertising and tiser’s bid for any impression is much smaller than its obtained the optimal (1-1/e) competitive ratio in the special budget. case of small bids. It has been open ever since whether Subsequently, AdWords has been studied under there is an algorithm for general bids better than the stochastic assumptions. Goel and Mehta [16] showed 0.5-competitive greedy algorithm. This paper presents a 0.5016-competitive algorithm for AdWords, answering this that assuming a random arrival order of the impressions 1− 1 open question on the positive end. The algorithm builds on and small bids, a e competitive ratio can be achieved several ingredients, including a combination of the online using the greedy algorithm: allocate each impression primal dual framework and the configuration linear pro- to the advertiser who would make the largest payment. -
Limits on Efficient Computation in the Physical World by Scott Joel
Limits on Efficient Computation in the Physical World by Scott Joel Aaronson Bachelor of Science (Cornell University) 2000 A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Computer Science in the GRADUATE DIVISION of the UNIVERSITY of CALIFORNIA, BERKELEY Committee in charge: Professor Umesh Vazirani, Chair Professor Luca Trevisan Professor K. Birgitta Whaley Fall 2004 The dissertation of Scott Joel Aaronson is approved: Chair Date Date Date University of California, Berkeley Fall 2004 Limits on Efficient Computation in the Physical World Copyright 2004 by Scott Joel Aaronson 1 Abstract Limits on Efficient Computation in the Physical World by Scott Joel Aaronson Doctor of Philosophy in Computer Science University of California, Berkeley Professor Umesh Vazirani, Chair More than a speculative technology, quantum computing seems to challenge our most basic intuitions about how the physical world should behave. In this thesis I show that, while some intuitions from classical computer science must be jettisoned in the light of modern physics, many others emerge nearly unscathed; and I use powerful tools from computational complexity theory to help determine which are which. In the first part of the thesis, I attack the common belief that quantum computing resembles classical exponential parallelism, by showing that quantum computers would face serious limitations on a wider range of problems than was previously known. In partic- ular, any quantum algorithm that solves the collision problem—that of deciding whether a sequence of n integers is one-to-one or two-to-one—must query the sequence Ω n1/5 times. -
David C. Parkes John A
David C. Parkes John A. Paulson School of Engineering and Applied Sciences, Harvard University, 33 Oxford Street, Cambridge, MA 02138, USA www.eecs.harvard.edu/~parkes December 2020 Citizenship: USA and UK Date of Birth: July 20, 1973 Education University of Oxford Oxford, U.K. Engineering and Computing Science, M.Eng (first class), 1995 University of Pennsylvania Philadelphia, PA Computer and Information Science, Ph.D., 2001 Advisor: Professor Lyle H. Ungar. Thesis: Iterative Combinatorial Auctions: Achieving Economic and Computational Efficiency Appointments George F. Colony Professor of Computer Science, 7/12-present Cambridge, MA Harvard University Co-Director, Data Science Initiative, 3/17-present Cambridge, MA Harvard University Area Dean for Computer Science, 7/13-6/17 Cambridge, MA Harvard University Harvard College Professor, 7/12-6/17 Cambridge, MA Harvard University Gordon McKay Professor of Computer Science, 7/08-6/12 Cambridge, MA Harvard University John L. Loeb Associate Professor of the Natural Sciences, 7/05-6/08 Cambridge, MA and Associate Professor of Computer Science Harvard University Assistant Professor of Computer Science, 7/01-6/05 Cambridge, MA Harvard University Lecturer of Operations and Information Management, Spring 2001 Philadelphia, PA The Wharton School, University of Pennsylvania Research Intern, Summer 2000 Hawthorne, NY IBM T.J.Watson Research Center Research Intern, Summer 1997 Palo Alto, CA Xerox Palo Alto Research Center 1 Other Appointments Member, 2019- Amsterdam, Netherlands Scientific Advisory Committee, CWI Member, 2019- Cambridge, MA Senior Common Room (SCR) of Lowell House Member, 2019- Berlin, Germany Scientific Advisory Board, Max Planck Inst. Human Dev. Co-chair, 9/17- Cambridge, MA FAS Data Science Masters Co-chair, 9/17- Cambridge, MA Harvard Business Analytics Certificate Program Co-director, 9/17- Cambridge, MA Laboratory for Innovation Science, Harvard University Affiliated Faculty, 4/14- Cambridge, MA Institute for Quantitative Social Science International Fellow, 4/14-12/18 Zurich, Switzerland Center Eng. -
Algorithmic Aspects of Connectivity, Allocation and Design Problems
ALGORITHMIC ASPECTS OF CONNECTIVITY, ALLOCATION AND DESIGN PROBLEMS A Thesis Presented to The Academic Faculty by Deeparnab Chakrabarty In Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in Algorithms, Combinatorics, and Optimization College of Computing Georgia Institute of Technology August 2008 ALGORITHMIC ASPECTS OF CONNECTIVITY, ALLOCATION AND DESIGN PROBLEMS Approved by: Professor Vijay V. Vazirani, Advisor Professor William Cook College of Computing School of Industrial Systems and Georgia Tech Engineering Georgia Tech Professor Robin Thomas Professor Adam Kalai School of Mathematics College of Computing Georgia Tech Georgia Tech Professor Prasad Tetali Date Approved: 15th May 2008 School of Mathematics Georgia Tech To those who probably will understand the least, but matter the most. iii ACKNOWLEDGEMENTS First and foremost, I thank my advisor, Vijay Vazirani, for his constant support, advice and help throughout these five years. I hope I have imbibed an of the infinite energy with which he does research. Thanks Vijay for everything! I thank Prasad Tetali for patiently listening to me ranting about my work and always advising me on how to proceed further. I will surely miss such an ideal sounding board. I thank Robin Thomas, William Cook and Adam Kalai for being on my committee. Thanks Robin for a careful reading of a paper of mine, Prof. Cook for being a careful reader of my thesis, and Adam for the chats and the margaritas! Many thanks to all the professors in Georgia Tech for their excellent lectures, both in and out of classes. The amount I have learnt in these five years is immeasurable. -
Approximation Algorithms Springer-Verlag Berlin Heidelberg Gmbh Vi Jay V
Approximation Algorithms Springer-Verlag Berlin Heidelberg GmbH Vi jay V. Vazirani Approximation Algorithms ~Springer Vi jay V. Vazirani Georgia Institute of Technology College of Computing 801 Atlantic Avenue Atlanta, GA 30332-0280 USA [email protected] http://www. cc.gatech.edu/fac/Vijay. Vazirani Corrected Second Printing 2003 Library of Congress Cataloging-in-Publication Data Vazirani, Vijay V. Approximation algorithms I Vi jay V. Vazirani. p.cm. Includes bibliographical references and index. ISBN 978-3-642-08469-0 ISBN 978-3-662-04565-7 (eBook) DOI 10.1007/978-3-662-04565-7 1. Computer algorithms. 2. Mathematical optimization. I. Title. QA76.g.A43 V39 2001 005-1-dc21 ACM Computing Classification (1998): F.1-2, G.l.2, G.l.6, G2-4 AMS Mathematics Classification (2000): 68-01; 68W05, 20, 25, 35,40; 68Q05-17, 25; 68R05, 10; 90-08; 90C05, 08, 10, 22, 27, 35, 46, 47, 59, 90; OSAOS; OSCOS, 12, 20, 38, 40, 45, 69, 70, 85, 90; 11H06; 15A03, 15, 18, 39,48 This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broad casting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer-Verlag Berlin Heidelberg GmbH. Violations are liable for prosecution under the German Copyright Law. -
Flows, Cuts and Integral Routing in Graphs - an Approximation Algorithmist’S Perspec- Tive
Flows, Cuts and Integral Routing in Graphs - an Approximation Algorithmist's Perspec- tive Julia Chuzhoy ∗ Abstract. Flow, cut and integral graph routing problems are among the most extensively studied in Operations Research, Optimization, Graph Theory and Computer Science. We survey known algorithmic results for these problems, including classical results and more recent developments, and discuss the major remaining open problems, with an emphasis on approximation algorithms. Mathematics Subject Classification (2010). Primary 68Q25; Secondary 68Q17, 68R05, 68R10. Keywords. Maximum flow, minimum cut, network routing, approximation algorithms, hardness of approximation, graph theory. 1. Introduction In this survey we consider flow, cut, and integral routing problems in graphs. These three types of problems are among the most extensively studied in Operations Research, Optimization, Graph Theory, and Computer Science. Problems of these types naturally arise in many applications, and algorithms for solving them are among the most valuable and powerful tools in algorithm design and analysis. In the classical maximum s{t flow problem, we are given an n-vertex graph G = (V; E), that can be either directed or undirected, with non-negative capacities c(e) on edges e 2 E, and two special vertices: s, called the source, and t, called the destination. Let P be the set of all paths connecting s to t in G. An s{t flow f is an assignment of non-negative values f(P ) to all paths P 2 P, such that for each edge e 2 E, the flow through e does not exceed its capacity c(e), that P P is, P :e2P f(P ) ≤ c(e). -
A Satisfiability Algorithm for AC0 961 Russel Impagliazzo, William Matthews and Ramamohan Paturi
A Satisfiability Algorithm for AC0 Russell Impagliazzo ∗ William Matthews † Ramamohan Paturi † Department of Computer Science and Engineering University of California, San Diego La Jolla, CA 92093-0404, USA January 2011 Abstract ing the size of the search space. In contrast, reducing We consider the problem of efficiently enumerating the problems such as planning or model-checking to the spe- satisfying assignments to AC0 circuits. We give a zero- cial cases of cnf Satisfiability or 3-sat can increase the error randomized algorithm which takes an AC0 circuit number of variables dramatically. On the other hand, as input and constructs a set of restrictions which cnf-sat algorithms (especially for small width clauses partitions {0, 1}n so that under each restriction the such as k-cnfs) have both been analyzed theoretically value of the circuit is constant. Let d denote the depth and implemented empirically with astounding success, of the circuit and cn denote the number of gates. This even when this overhead is taken into account. For some algorithm runs in time |C|2n(1−µc,d) where |C| is the domains of structured cnf formulas that arise in many d−1 applications, state-of-the-art SAT-solvers can handle up size of the circuit for µc,d ≥ 1/O[lg c + d lg d] with probability at least 1 − 2−n. to hundreds of thousands of variables and millions of As a result, we get improved exponential time clauses [11]. Meanwhile, very few results are known ei- algorithms for AC0 circuit satisfiability and for counting ther theoretically or empirically about the difficulty of solutions. -
Classical Verification and Blind Delegation of Quantum
Classical Verification and Blind Delegation of Quantum Computations by Urmila M. Mahadev A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Computer Science in the Graduate Division of the University of California, Berkeley Committee in charge: Professor Umesh Vazirani, Chair Professor Satish Rao Professor Nikhil Srivastava Spring 2018 Classical Verification and Blind Delegation of Quantum Computations Copyright 2018 by Urmila M. Mahadev 1 Abstract Classical Verification and Blind Delegation of Quantum Computations by Urmila M. Mahadev Doctor of Philosophy in Computer Science University of California, Berkeley Professor Umesh Vazirani, Chair In this dissertation, we solve two open questions. First, can the output of a quantum computation be verified classically? We give the first protocol for provable classical verifica- tion of efficient quantum computations, depending only on the assumption that the learning with errors problem is post-quantum secure. The second question, which is related to verifiability and is often referred to as blind computation, asks the following: can a classical client delegate a desired quantum compu- tation to a remote quantum server while hiding all data from the server? This is especially relevant to proposals for quantum computing in the cloud. For classical computations, this task is achieved by the celebrated result of fully homomorphic encryption ([23]). We prove an analogous result for quantum computations by showing that certain classical homomorphic encryption schemes, when used in a different manner, are able to homomorphically evaluate quantum circuits. While we use entirely different techniques to construct the verification and homomorphic encryption protocols, they both rely on the same underlying cryptographic primitive of trapdoor claw-free functions.