From Convex Optimization to Mdps: a Review of First-Order, Second
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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. -
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). -
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 .................................................................................................................... -
Stochastic Combinatorial Optimization with Controllable Risk Aversion Level
Stochastic Combinatorial Optimization with Controllable Risk Aversion Level Anthony Man–Cho So Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, N. T., Hong Kong email: [email protected] Jiawei Zhang Department of Information, Operations, and Management Sciences, Stern School of Business, New York University, New York, NY 10012, USA email: [email protected] Yinyu Ye Department of Management Science and Engineering and, by courtesy, Electrical Engineering, Stanford University, Stanford, CA 94305, USA email: [email protected] Most of the recent work on 2–stage stochastic combinatorial optimization problems have focused on the min- imization of the expected cost or the worst–case cost of the solution. Those two objectives can be viewed as two extreme ways of handling risk. In this paper we propose to use an one–parameter family of functionals to interpolate between them. Although such a family has been used in the mathematical finance and stochastic programming literature before, its use in the context of approximation algorithms seems new. We show that under standard assumptions, a broad class of risk–adjusted 2–stage stochastic programs can be efficiently treated by the Sample Average Approximation (SAA) method. In particular, our result shows that it is computationally feasible to incorporate some degree of robustness even when the underlying distribution can only be accessed in a black–box fashion. We also show that when combined with suitable rounding procedures, our result yields new approximation algorithms for many risk–adjusted 2–stage stochastic combinatorial optimization problems under the black–box setting. -
Opf)P in OPERATIONS RESEARCH
APPLICATION OF MATHEMATICAL PROGRAMMING DISSERTATION SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE AWARD OF THE DEGREE OF iWasiter of ^i)Uo«opf)p IN OPERATIONS RESEARCH By TEG ALAM Under the Supervision of DR. A. BARI DEPARTMENT OF STATISTICS & OPERATIONS-RESEARCH ALIGARH MUSLIM UNIVERSITY ALIGARH (INDIA) 2001 '^•^ P5.-32^^ ^, DS3200 DEPARTMENT OF STATISTICS & OPERATION RESEARCI ALIGARH MUSLIM UNIVERSITY (Dr. X ^ari ALIGARH - 202002 -INDIA Ph.D (AUg) ^hone: 0571-701251 (O) "^ 0571-700112 (R) Dated: OE(RTlTICA'VE Certified that the dissertation entitled "Application of Mathematical Programming" is carried out by Tcg Alaitl under my supervision. The work is sufficient for the requirement of degree of Master of Philosophy in Operations Research. ((Dr. A. (Bari) Supervisor Univ. Exchange: (0571) 700920 -23 Extns:419, 421,422, 441 Fax:+91-571-400528 This Dissertation entitled ''^Application of Mathematical programming''' is submitted to the Aligarh Muslim University, Aligarh, for the partial fiilfillment of the degree of M.Phil in OperationsResearch. Mathematical programming is concerned with the determination of a minimum or a maximum of a function of several variables, which are required to satisfy a number of constraints. Such solutions are sought in diverse fields; including engineering, Operations Research, Management Science, numerical analysis and economics etc. This mamuscript consists of five chapters. Chapter-1 deals with the brief history of Mathematical Programming. It also contains numerous applications of Mathematical Programming. Chapter-2 gives an introduction of Transportation problem and devoted to extensions and methods of solutions. A numerical example and Relation of Transportation problems with Network problems are also discussed. Chapter - 3 gives an introduction of Game theory. -
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. -
Optima 82 Publishes the Obituary of Paul Tseng by His Friends Affected by the Proposed Change; Only Their Subtitles Would Change
OPTIMA Mathematical Programming Society Newsletter 82 Steve Wright MPS-sponsored meetings: the International Conference on Stochas- MPS Chair’s Column tic Programming (ICSP) XII (Halifax, August 14–20), the Interna- tional Conference on Engineering Optimization (Lisbon, September 6–9), and the IMA Conference on Numerical Linear Algebra and March 16, 2010. You should recently have received a letter con- Optimization (Birmingham, September 13–15). cerning a possible change of name for MPS, to “Mathematical Op- timization Society”. This issue has been discussed in earnest since ISMP 2009, where it was raised at the Council and Business meet- ings. Some of you were kind enough to send me your views follow- Note from the Editors ing the mention in my column in Optima 80. Many (including me) believe that the term “optimization” is more widely recognized and The topic of this issue of Optima is Mechanism Design –aNobel better understood as an appellation for our field than the current prize winning theoretical field of economics. name, both among those working in the area and our colleagues We present the main article by Jay Sethuraman, which introduces in other disciplines. Others believe that the current name should the main concepts and existence results for some of the models be retained, as it has the important benefits of tradition, branding, arising in mechanism design theory. The discussion column by Garud and name recognition. To ensure archival continuity in the literature, Iyengar and Anuj Kumar address a specific example of such a model the main titles of our journals Mathematical Programming, Series A which can be solved by the means of optimization. -
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. -
Mathematics People
NEWS Mathematics People Tardos Named Goldfarb and Nocedal Kovalevsky Lecturer Awarded 2017 von Neumann Éva Tardos of Cornell University Theory Prize has been chosen as the 2018 AWM- SIAM Sonia Kovalevsky Lecturer by Donald Goldfarb of Columbia the Association for Women in Math- University and Jorge Nocedal of ematics (AWM) and the Society for Northwestern University have been Industrial and Applied Mathematics awarded the 2017 John von Neu- (SIAM). She was honored for her “dis- mann Theory Prize by the Institute tinguished scientific contributions for Operations Research and the to the efficient methods for com- Management Sciences (INFORMS). binatorial optimization problems According to the prize citation, “The Éva Tardos on graphs and networks, and her award recognizes the seminal con- work on issues at the interface of tributions that Donald Goldfarb computing and economics.” According to the prize cita- Jorge Nocedal and Jorge Nocedal have made to the tion, she is considered “one of the leaders in defining theory and applications of nonlinear the area of algorithmic game theory, in which algorithms optimization over the past several decades. These contri- are designed in the presence of self-interested agents butions cover a full range of topics, going from modeling, governed by incentives and economic constraints.” With to mathematical analysis, to breakthroughs in scientific Tim Roughgarden, she was awarded the 2012 Gödel Prize computing. Their work on the variable metric methods of the Association for Computing Machinery (ACM) for a paper “that shaped the field of algorithmic game theory.” (BFGS and L-BFGS, respectively) has been extremely in- She received her PhD in 1984 from Eötvös Loránd Univer- fluential.” sity. -
Arxiv:1411.2129V1 [Math.OC]
INTERIOR-POINT ALGORITHMS FOR CONVEX OPTIMIZATION BASED ON PRIMAL-DUAL METRICS TOR MYKLEBUST, LEVENT TUNC¸EL Abstract. We propose and analyse primal-dual interior-point algorithms for convex opti- mization problems in conic form. The families of algorithms we analyse are so-called short- step algorithms and they match the current best iteration complexity bounds for primal-dual symmetric interior-point algorithm of Nesterov and Todd, for symmetric cone programming problems with given self-scaled barriers. Our results apply to any self-concordant barrier for any convex cone. We also prove that certain specializations of our algorithms to hyperbolic cone programming problems (which lie strictly between symmetric cone programming and gen- eral convex optimization problems in terms of generality) can take advantage of the favourable special structure of hyperbolic barriers. We make new connections to Riemannian geometry, integrals over operator spaces, Gaussian quadrature, and strengthen the connection of our algorithms to quasi-Newton updates and hence first-order methods in general. arXiv:1411.2129v1 [math.OC] 8 Nov 2014 Date: November 7, 2014. Key words and phrases. primal-dual interior-point methods, convex optimization, variable metric methods, local metric, self-concordant barriers, Hessian metric, polynomial-time complexity; AMS subject classification (MSC): 90C51, 90C22, 90C25, 90C60, 90C05, 65Y20, 52A41, 49M37, 90C30. Tor Myklebust: Department of Combinatorics and Optimization, Faculty of Mathematics, University of Wa- terloo, Waterloo, Ontario N2L 3G1, Canada (e-mail: [email protected]). Research of this author was supported in part by an NSERC Doctoral Scholarship, ONR Research Grant N00014-12-10049, and a Dis- covery Grant from NSERC.