George Dantzig and Leonid Tributes to Khachiyan George Dantzig: a Personal Perspective Walter Murray
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Arkadi Nemirovski (PDF)
Arkadi Nemirovski Mr. Chancellor, I present Arkadi Nemirovski. For more than thirty years, Arkadi Nemirovski has been a leader in continuous optimization. He has played central roles in three of the major breakthroughs in optimization, namely, the ellipsoid method for convex optimization, the extension of modern interior-point methods to convex optimization, and the development of robust optimization. All of these contributions have had tremendous impact, going significantly beyond the original domain of the discoveries in their theoretical and practical consequences. In addition to his outstanding work in optimization, Professor Nemirovski has also made major contributions in the area of nonparametric statistics. Even though the most impressive part of his work is in theory, every method, every algorithm he proposes comes with a well-implemented computer code. Professor Nemirovski is widely admired not only for his brilliant scientific contributions, but also for his gracious humility, kindness, generosity, and his dedication to students and colleagues. Professor Nemirovski has held chaired professorships and many visiting positions at top research centres around the world, including an adjunct professor position in the Department of Combinatorics and Optimization at Waterloo from 2000-2004. Since 2005, Professor Nemirovski has been John Hunter Professor in the School of Industrial and Systems Engineering at the Georgia Institute of Technology. Among many previous honours, he has received the Fulkerson Prize from the American Mathematical Society and the Mathematical Programming Society in 1982, the Dantzig Prize from the Society for Industrial and Applied Mathematics and the Mathematical Programming Society in 1991, and the John von Neumann Theory Prize from the Institute for Operations Research and the Management Sciences in 2003. -
Simplex Algorithm
CAP 4630 Artificial Intelligence Instructor: Sam Ganzfried [email protected] 1 HW2 • Due yesterday (10/18) at 2pm on Moodle • It is ok to work with one partner for homework 2. Must include document stating whom you worked with and describe extent of collaboration. This policy may be modified for future assignments. • Remember late day policy. – 5 total late days 2 Schedule • 10/12: Wrap-up logic (logical inference), start optimization (integer, linear optimization) • 10/17: Continue optimization (integer, linear optimization) • 10/19: Wrap up optimization (nonlinear optimization), go over homework 1 (and parts of homework 2 if all students have turned it in by start of class), midterm review • 10/24: Midterm • 10/26: Planning 3 Minesweeper • Minesweeper is NP-complete • http://simon.bailey.at/random/kaye.minesweeper.pdf 4 NP-completeness • Consider Sudoku, an example of a problem that is easy to verify, but whose answer may be difficult to compute. Given a partially filled-in Sudoku grid, of any size, is there at least one legal solution? A proposed solution is easily verified, and the time to check a solution grows slowly (polynomially) as the grid gets bigger. However, all known algorithms for finding solutions take, for difficult examples, time that grows exponentially as the grid gets bigger. So Sudoku is in NP (quickly checkable) but does not seem to be in P (quickly solvable). Thousands of other problems seem similar, fast to check but slow to solve. Researchers have shown that a fast solution to any one of these problems could be used to build a quick solution to all the others, a property called NP-completeness. -
2019 AMS Prize Announcements
FROM THE AMS SECRETARY 2019 Leroy P. Steele Prizes The 2019 Leroy P. Steele Prizes were presented at the 125th Annual Meeting of the AMS in Baltimore, Maryland, in January 2019. The Steele Prizes were awarded to HARUZO HIDA for Seminal Contribution to Research, to PHILIppE FLAJOLET and ROBERT SEDGEWICK for Mathematical Exposition, and to JEFF CHEEGER for Lifetime Achievement. Haruzo Hida Philippe Flajolet Robert Sedgewick Jeff Cheeger Citation for Seminal Contribution to Research: Hamadera (presently, Sakai West-ward), Japan, he received Haruzo Hida an MA (1977) and Doctor of Science (1980) from Kyoto The 2019 Leroy P. Steele Prize for Seminal Contribution to University. He did not have a thesis advisor. He held po- Research is awarded to Haruzo Hida of the University of sitions at Hokkaido University (Japan) from 1977–1987 California, Los Angeles, for his highly original paper “Ga- up to an associate professorship. He visited the Institute for Advanced Study for two years (1979–1981), though he lois representations into GL2(Zp[[X ]]) attached to ordinary cusp forms,” published in 1986 in Inventiones Mathematicae. did not have a doctoral degree in the first year there, and In this paper, Hida made the fundamental discovery the Institut des Hautes Études Scientifiques and Université that ordinary cusp forms occur in p-adic analytic families. de Paris Sud from 1984–1986. Since 1987, he has held a J.-P. Serre had observed this for Eisenstein series, but there full professorship at UCLA (and was promoted to Distin- the situation is completely explicit. The methods and per- guished Professor in 1998). -
Computational Geometry Lecture Notes1 HS 2012
Computational Geometry Lecture Notes1 HS 2012 Bernd Gärtner <[email protected]> Michael Hoffmann <[email protected]> Tuesday 15th January, 2013 1Some parts are based on material provided by Gabriel Nivasch and Emo Welzl. We also thank Tobias Christ, Anna Gundert, and May Szedlák for pointing out errors in preceding versions. Contents 1 Fundamentals 7 1.1 ModelsofComputation ............................ 7 1.2 BasicGeometricObjects. 8 2 Polygons 11 2.1 ClassesofPolygons............................... 11 2.2 PolygonTriangulation . 15 2.3 TheArtGalleryProblem ........................... 19 3 Convex Hull 23 3.1 Convexity.................................... 24 3.2 PlanarConvexHull .............................. 27 3.3 Trivialalgorithms ............................... 29 3.4 Jarvis’Wrap .................................. 29 3.5 GrahamScan(SuccessiveLocalRepair) . .... 31 3.6 LowerBound .................................. 33 3.7 Chan’sAlgorithm................................ 33 4 Line Sweep 37 4.1 IntervalIntersections . ... 38 4.2 SegmentIntersections . 38 4.3 Improvements.................................. 42 4.4 Algebraic degree of geometric primitives . ....... 42 4.5 Red-BlueIntersections . .. 45 5 Plane Graphs and the DCEL 51 5.1 TheEulerFormula............................... 52 5.2 TheDoubly-ConnectedEdgeList. .. 53 5.2.1 ManipulatingaDCEL . 54 5.2.2 GraphswithUnboundedEdges . 57 5.2.3 Remarks................................. 58 3 Contents CG 2012 6 Delaunay Triangulations 61 6.1 TheEmptyCircleProperty . 64 6.2 TheLawsonFlipalgorithm -
Institute for Pure and Applied Mathematics, UCLA Award/Institution #0439872-013151000 Annual Progress Report for 2009-2010 August 1, 2011
Institute for Pure and Applied Mathematics, UCLA Award/Institution #0439872-013151000 Annual Progress Report for 2009-2010 August 1, 2011 TABLE OF CONTENTS EXECUTIVE SUMMARY 2 A. PARTICIPANT LIST 3 B. FINANCIAL SUPPORT LIST 4 C. INCOME AND EXPENDITURE REPORT 4 D. POSTDOCTORAL PLACEMENT LIST 5 E. INSTITUTE DIRECTORS‘ MEETING REPORT 6 F. PARTICIPANT SUMMARY 12 G. POSTDOCTORAL PROGRAM SUMMARY 13 H. GRADUATE STUDENT PROGRAM SUMMARY 14 I. UNDERGRADUATE STUDENT PROGRAM SUMMARY 15 J. PROGRAM DESCRIPTION 15 K. PROGRAM CONSULTANT LIST 38 L. PUBLICATIONS LIST 50 M. INDUSTRIAL AND GOVERNMENTAL INVOLVEMENT 51 N. EXTERNAL SUPPORT 52 O. COMMITTEE MEMBERSHIP 53 P. CONTINUING IMPACT OF PAST IPAM PROGRAMS 54 APPENDIX 1: PUBLICATIONS (SELF-REPORTED) 2009-2010 58 Institute for Pure and Applied Mathematics, UCLA Award/Institution #0439872-013151000 Annual Progress Report for 2009-2010 August 1, 2011 EXECUTIVE SUMMARY Highlights of IPAM‘s accomplishments and activities of the fiscal year 2009-2010 include: IPAM held two long programs during 2009-2010: o Combinatorics (fall 2009) o Climate Modeling (spring 2010) IPAM‘s 2010 winter workshops continued the tradition of focusing on emerging topics where Mathematics plays an important role: o New Directions in Financial Mathematics o Metamaterials: Applications, Analysis and Modeling o Mathematical Problems, Models and Methods in Biomedical Imaging o Statistical and Learning-Theoretic Challenges in Data Privacy IPAM sponsored reunion conferences for four long programs: Optimal Transport, Random Shapes, Search Engines and Internet MRA IPAM sponsored three public lectures since August. Noga Alon presented ―The Combinatorics of Voting Paradoxes‖ on October 5, 2009. Pierre-Louis Lions presented ―On Mean Field Games‖ on January 5, 2010. -
Prizes and Awards Session
PRIZES AND AWARDS SESSION Wednesday, July 12, 2021 9:00 AM EDT 2021 SIAM Annual Meeting July 19 – 23, 2021 Held in Virtual Format 1 Table of Contents AWM-SIAM Sonia Kovalevsky Lecture ................................................................................................... 3 George B. Dantzig Prize ............................................................................................................................. 5 George Pólya Prize for Mathematical Exposition .................................................................................... 7 George Pólya Prize in Applied Combinatorics ......................................................................................... 8 I.E. Block Community Lecture .................................................................................................................. 9 John von Neumann Prize ......................................................................................................................... 11 Lagrange Prize in Continuous Optimization .......................................................................................... 13 Ralph E. Kleinman Prize .......................................................................................................................... 15 SIAM Prize for Distinguished Service to the Profession ....................................................................... 17 SIAM Student Paper Prizes .................................................................................................................... -
Customized Book List Computer Science
ABCD springer.com Springer Customized Book List Computer Science FRANKFURT BOOKFAIR 2007 springer.com/booksellers Computer Science 1 K. Aberer, Korea Advanced Institute of Science and Technolo- A. Abraham, Norwegian University of Science and Technology, gy, Korea; N. Noy, Stanford University, Stanford, CA, USA; D. Alle- Trondheim, Norway; Y. Dote, Muroran Institute of Technology, Transactions on Computational mang, TopQuadrant, CA, USA; K.-I. Lee, Saltlux Inc., Korea; L. Muroran, Japan Nixon, Free University Berlin, Germany; J. Goldbeck, University of Systems Biology VIII Maryland, MD, USA; P. Mika, Yahoo! Research Barcelona, Spain; D. Maynard, University of Sheffield, United Kingdom,; R. Mizoguchi, Engineering Hybrid Soft Computing Osaka University, Japan,; G. Schreiber, Free University Amster- dam, Netherlands,; P. Cudré-Mauroux, EPFL, Switzerland, (Eds.) Systems The LNCS journal Transactions on Computation- al Systems Biology is devoted to inter- and multi- disciplinary research in the fields of computer sci- The Semantic Web This book is focused on the latest technologies re- ence and life sciences and supports a paradigmat- 6th International Semantic Web Conference, 2nd Asian Se- lated to Hybrid Soft Computing targeting academia, ic shift in the techniques from computer and infor- mantic Web Conference, ISWC 2007 + ASWC 2007, Busan, Ko- scientists, researchers, and graduate students. mation science to cope with the new challenges aris- rea, November 11-15, 2007, Proceedings ing from the systems oriented point of view of bio- Features -
How Do Exponential Size Solutions Arise in Semidefinite Programming?
How do exponential size solutions arise in semidefinite programming? G´abor Pataki, Aleksandr Touzov ∗ June 30, 2021 Abstract Semidefinite programs (SDPs) are some of the most popular and broadly applicable optimiza- tion problems to emerge in the last thirty years. A curious pathology of SDPs, illustrated by a classical example of Khachiyan, is that their solutions may need exponential space to even write down. Exponential size solutions are the main obstacle to solve a long standing open problem: can we decide feasibility of SDPs in polynomial time? The consensus seems to be that large size solutions in SDPs are rare. Here we prove that they are actually quite common: a linear change of variables transforms every strictly feasible SDP into a Khachiyan type SDP, in which the leading variables are large. As to \how large", that depends on the singularity degree of a dual problem. Further, we present some SDPs in which large solutions appear naturally, without any change of variables. We also partially answer the question: how do we represent such large solutions in polynomial space? Key words: semidefinite programming; exponential size solutions; Khachiyan's example; facial reduction; singularity degree MSC 2010 subject classification: Primary: 90C22, 49N15; secondary: 52A40 OR/MS subject classification: Primary: convexity; secondary: programming-nonlinear-theory 1 Introduction Contents 1 Introduction 1 1.1 Notation and preliminaries..................................5 2 Main results and proofs6 2.1 Reformulating (P) and statement of Theorem1.......................6 -
Bcol Research Report 14.02
BCOL RESEARCH REPORT 14.02 Industrial Engineering & Operations Research University of California, Berkeley, CA 94720-1777 Forthcoming in Discrete Optimization SUPERMODULAR COVERING KNAPSACK POLYTOPE ALPER ATAMTURK¨ AND AVINASH BHARDWAJ Abstract. The supermodular covering knapsack set is the discrete upper level set of a non-decreasing supermodular function. Submodular and supermodular knapsack sets arise naturally when modeling utilities, risk and probabilistic constraints on discrete variables. In a recent paper Atamt¨urkand Narayanan [6] study the lower level set of a non-decreasing submodular function. In this complementary paper we describe pack inequalities for the super- modular covering knapsack set and investigate their separation, extensions and lifting. We give sequence-independent upper bounds and lower bounds on the lifting coefficients. Furthermore, we present a computational study on using the polyhedral results derived for solving 0-1 optimization problems over conic quadratic constraints with a branch-and-cut algorithm. Keywords : Conic integer programming, supermodularity, lifting, probabilistic cov- ering knapsack constraints, branch-and-cut algorithms Original: September 2014, Latest: May 2015 This research has been supported, in part, by grant FA9550-10-1-0168 from the Office of Assistant Secretary Defense for Research and Engineering. 2 ALPER ATAMTURK¨ AND AVINASH BHARDWAJ 1. Introduction A set function f : 2N ! R is supermodular on finite ground set N [22] if f(S) + f(T ) ≤ f(S [ T ) + f(S \ T ); 8 S; T ⊆ N: By abuse of notation, for S ⊆ N we refer to f(S) also as f(χS), where χS denotes the binary characteristic vector of S. Given a non-decreasing supermodular function f on N and d 2 R, the supermodular covering knapsack set is defined as n o K := x 2 f0; 1gN : f(x) ≥ d ; that is, the discrete upper level set of f. -
Decomposition, Approximation, and Coloring of Odd-Minor-Free Graphs
Decomposition, Approximation, and Coloring of Odd-Minor-Free Graphs Erik D. Demaine∗ MohammadTaghi Hajiaghayiy Ken-ichi Kawarabayashiz Abstract between the pieces. For example, many optimization prob- We prove two structural decomposition theorems about graphs ex- lems can be solved exactly on graphs of bounded treewidth; cluding a fixed odd minor H, and show how these theorems can what graphs can be partitioned into a small number k of be used to obtain approximation algorithms for several algorithmic bounded-treewidth pieces? In many cases, each piece gives problems in such graphs. Our decomposition results provide new a lower/upper bound on the optimal solution for the entire structural insights into odd-H-minor-free graphs, on the one hand graph, so solving the problem exactly in each piece gives a generalizing the central structural result from Graph Minor The- k-approximation to the problem. Such a decomposition into ory, and on the other hand providing an algorithmic decomposition bounded-treewidth graphs would also be practical, as many into two bounded-treewidth graphs, generalizing a similar result for NP-hard optimization problems are now solved in practice minors. As one example of how these structural results conquer dif- using dynamic programming on low-treewidth graphs; see, ficult problems, we obtain a polynomial-time 2-approximation for e.g., [Bod05, Ami01, Tho98]. Recently, this decomposi- vertex coloring in odd-H-minor-free graphs, improving on the pre- tion approach has been successfully used for graph coloring, 1−" vious O(jV (H)j)-approximation for such graphs and generalizing which is inapproximable within n for any " > 0 unless the previous 2-approximation for H-minor-free graphs. -
Data-Driven Methods and Applications for Optimization Under Uncertainty and Rare-Event Simulation
Data-Driven Methods and Applications for Optimization under Uncertainty and Rare-Event Simulation by Zhiyuan Huang A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Industrial and Operations Engineering) in The University of Michigan 2020 Doctoral Committee: Assistant Professor Ruiwei Jiang, Co-chair Associate Professor Henry Lam, Co-chair Associate Professor Eunshin Byon Assistant Professor Gongjun Xu Assistant Professor Ding Zhao Zhiyuan Huang [email protected] ORCID iD: 0000-0003-1284-2128 c Zhiyuan Huang 2020 Dedicated to my parents Weiping Liu and Xiaolei Huang ii ACKNOWLEDGEMENTS First of all, I am deeply thankful to my advisor Professor Henry Lam for his guidance and support throughout my Ph.D. experience. It has been one of the greatest honor of my life working with him as a graduate student. His wisdom, kindness, dedication, and passion have encouraged me to overcome difficulties and to complete my dissertation. I also would like to thank my dissertation committee members. I want to thank the committee co-chair Professor Ruiwei Jiang for his support in my last two Ph.D. years. I am also grateful to Professor Ding Zhao for his consistent help and collaboration. My appreciation also goes to Professor Gongjun Xu for his valuable comments on my dissertation. I would like to thank Professor Eunshin Byon for being helpful both academically and personally. Next, I want to thank other collaborators in my Ph.D. studies. I am very fortunate to encounter great mentor and collaborator Professor Jeff Hong, who made great advice on Chapter 2 of this dissertation. -
Norbert Wiener Prizes in Applied Mathematics
FROM THE AMS SECRETARY 2019 Norbert Wiener Prizes in Applied Mathematics The 2019 Norbert Wiener Prizes in Applied Mathematics were presented at the 125th Annual Meeting of the AMS in Baltimore, Maryland, in January 2019. The prizes were awarded to MARSHA BERGER and to ARKADI NEMIROVSKI. Citation: Marsha Berger to simulate tsunamis, debris flows, and dam breaks, among The 2019 Norbert Wiener Prize other applications. in Applied Mathematics is Biographical Note: Marsha Berger awarded to Marsha Berger for her fundamental contributions Marsha Berger received her PhD in computer science from to Adaptive Mesh Refinement Stanford in 1982. She started as a postdoc at the Courant Institute of Mathematical Sciences at NYU, and is currently and to Cartesian mesh tech- a Silver Professor in the computer science department, niques for automating the sim- where she has been since 1985. ulation of compressible flows She is a frequent visitor to NASA Ames, where she has in complex geometry. spent every summer since 1990 and several sabbaticals. Her In solving partial differen- honors include membership in the National Academy of tial equations, Adaptive Mesh Sciences, the National Academy of Engineering, and the Marsha Berger Refinement (AMR) algorithms American Academy of Arts and Science. She is a fellow of can improve the accuracy of a the Society for Industrial and Applied Mathematics. Berger solution by locally and dynam- was a recipient of the Institute of Electrical and Electronics ically resolving complex features of a simulation. Marsha Engineers Fernbach Award and was part of the team that Berger is one of the inventors of AMR.