40 DM12 Abstracts
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
On Likely Solutions of the Stable Matching Problem with Unequal
ON LIKELY SOLUTIONS OF THE STABLE MATCHING PROBLEM WITH UNEQUAL NUMBERS OF MEN AND WOMEN BORIS PITTEL Abstract. Following up a recent work by Ashlagi, Kanoria and Leshno, we study a stable matching problem with unequal numbers of men and women, and independent uniform preferences. The asymptotic formulas for the expected number of stable matchings, and for the probabilities of one point–concentration for the range of husbands’ total ranks and for the range of wives’ total ranks are obtained. 1. Introduction and main results Consider the set of n1 men and n2 women facing a problem of selecting a marriage partner. For n1 = n2 = n, a marriage M is a matching (bijection) between the two sets. It is assumed that each man and each woman has his/her preferences for a marriage partner, with no ties allowed. That is, there are given n permutations σj of the men set and n permutations ρj of the women set, each σj (ρj resp.) ordering the women set (the men set resp.) according to the desirability degree of a woman (a man) as a marriage partner for man j (woman j). A marriage is called stable if there is no unmarried pair (a man, a woman) who prefer each other to their respective partners in the marriage. A classic theorem, due to Gale and Shapley [4], asserts that, given any system of preferences {ρj,σj}j∈[n], there exists at least one stable marriage M. arXiv:1701.08900v2 [math.CO] 13 Feb 2017 The proof of this theorem is algorithmic. A bijection is constructed in steps such that at each step every man not currently on hold makes a pro- posal to his best choice among women who haven’t rejected him before, and the chosen woman either provisionally puts the man on hold or rejects him, based on comparison of him to her current suitor if she has one already. -
On the Effi Ciency of Stable Matchings in Large Markets Sangmok Lee
On the Effi ciency of Stable Matchings in Large Markets SangMok Lee Leeat Yarivyz August 22, 2018 Abstract. Stability is often the goal for matching clearinghouses, such as those matching residents to hospitals, students to schools, etc. We study the wedge between stability and utilitarian effi ciency in large one-to-one matching markets. We distinguish between stable matchings’average effi ciency (or, effi ciency per-person), which is maximal asymptotically for a rich preference class, and their aggregate effi ciency, which is not. The speed at which average effi ciency of stable matchings converges to its optimum depends on the underlying preferences. Furthermore, for severely imbalanced markets governed by idiosyncratic preferences, or when preferences are sub-modular, stable outcomes may be average ineffi cient asymptotically. Our results can guide market designers who care about effi ciency as to when standard stable mechanisms are desirable and when new mechanisms, or the availability of transfers, might be useful. Keywords: Matching, Stability, Effi ciency, Market Design. Department of Economics, Washington University in St. Louis, http://www.sangmoklee.com yDepartment of Economics, Princeton University, http://www.princeton.edu/yariv zWe thank Federico Echenique, Matthew Elliott, Aytek Erdil, Mallesh Pai, Rakesh Vohra, and Dan Wal- ton for very useful comments and suggestions. Euncheol Shin provided us with superb research assistance. Financial support from the National Science Foundation (SES 0963583) and the Gordon and Betty Moore Foundation (through grant 1158) is gratefully acknowledged. On the Efficiency of Stable Matchings in Large Markets 1 1. Introduction 1.1. Overview. The design of most matching markets has focused predominantly on mechanisms in which only ordinal preferences are specified: the National Resident Match- ing Program (NRMP), clearinghouses for matching schools and students in New York City and Boston, and many others utilize algorithms that implement a stable matching correspond- ing to reported rank preferences. -
Matchings and Games on Networks
Matchings and games on networks by Linda Farczadi A thesis presented to the University of Waterloo in fulfilment of the thesis requirement for the degree of Doctor of Philosophy in Combinatorics and Optimization Waterloo, Ontario, Canada, 2015 c Linda Farczadi 2015 Author's Declaration I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, including any required final revisions, as accepted by my examiners. I understand that my thesis may be made electronically available to the public. ii Abstract We investigate computational aspects of popular solution concepts for different models of network games. In chapter 3 we study balanced solutions for network bargaining games with general capacities, where agents can participate in a fixed but arbitrary number of contracts. We fully characterize the existence of balanced solutions and provide the first polynomial time algorithm for their computation. Our methods use a new idea of reducing an instance with general capacities to an instance with unit capacities defined on an auxiliary graph. This chapter is an extended version of the conference paper [32]. In chapter 4 we propose a generalization of the classical stable marriage problem. In our model the preferences on one side of the partition are given in terms of arbitrary bi- nary relations, that need not be transitive nor acyclic. This generalization is practically well-motivated, and as we show, encompasses the well studied hard variant of stable mar- riage where preferences are allowed to have ties and to be incomplete. Our main result shows that deciding the existence of a stable matching in our model is NP-complete. -
Hypercubes Are Determined by Their Distance Spectra 3
HYPERCUBES ARE DETERMINED BY THEIR DISTANCE SPECTRA JACK H. KOOLEN♦, SAKANDER HAYAT♠, AND QUAID IQBAL♣ Abstract. We show that the d-cube is determined by the spectrum of its distance matrix. 1. Introduction For undefined terms, see next section. For integers n 2 and d 2, the Ham- ming graph H(d, n) has as vertex set, the d-tuples with elements≥ from≥0, 1, 2,...,n 1 , with two d-tuples are adjacent if and only if they differ only in one{ coordinate.− For} a positive integer d, the d-cube is the graph H(d, 2). In this paper, we show that the d-cube is determined by its distance spectrum, see Theorem 5.4. Observe that the d-cube has exactly three distinct distance eigenvalues. Note that the d-cube is not determined by its adjacency spectrum as the Hoffman graph [11] has the same adjacency spectrum as the 4-cube and hence the cartesian product of (d 4)-cube and the Hoffman graph has the same adjacency spectrum − as the d-cube (for d 4, where the 0-cube is just K1). This also implies that the complement of the d-cube≥ is not determined by its distance spectrum, if d 4. ≥ There are quite a few papers on matrices of graphs with a few distinct eigenvalues. An important case is, when the Seidel matrix of a graph has exactly two distinct eigenvalues is very much studied, see, for example [18]. Van Dam and Haemers [20] characterized the graphs whose Laplacian matrix has two distinct nonzero eigenval- ues. -
PDF Reference
NetworkX Reference Release 1.2 Aric Hagberg, Dan Schult, Pieter Swart August 01, 2010 CONTENTS 1 Introduction 1 1.1 Who uses NetworkX?..........................................1 1.2 The Python programming language...................................1 1.3 Free software...............................................1 1.4 Goals...................................................1 1.5 History..................................................2 2 Overview 3 2.1 NetworkX Basics.............................................3 2.2 Nodes and Edges.............................................4 3 Graph types 9 3.1 Which graph class should I use?.....................................9 3.2 Basic graph types.............................................9 4 Algorithms 133 4.1 Bipartite................................................. 133 4.2 Blockmodeling.............................................. 135 4.3 Boundary................................................. 136 4.4 Centrality................................................. 137 4.5 Clique.................................................. 145 4.6 Clustering................................................ 147 4.7 Components............................................... 150 4.8 Cores................................................... 158 4.9 Cycles.................................................. 158 4.10 Directed Acyclic Graphs......................................... 159 4.11 Distance Measures............................................ 161 4.12 Eulerian................................................. -
Class Descriptions—Week 5, Mathcamp 2016
CLASS DESCRIPTIONS|WEEK 5, MATHCAMP 2016 Contents 9:10 Classes 2 Building Groups out of Other Groups 2 More Problem Solving: Polynomials 2 The Hairy and Still Lonely Torus 2 Turning Points in the History of Mathematics 4 Why Aren't We Learning This: Fun Stuff in Statistics 4 10:10 Classes 4 A Very Difficult Definite Integral 4 Homotopy (Co)limits 5 Scandalous Curves 5 Special Relativity 5 String Theory 6 The Magic of Determinants 6 The Mathematical ABCs 7 The Stable Marriage Problem 7 Quadratic Reciprocity 7 11:10 Classes 8 Benford's Law 8 Egyptian Fractions 8 Gambling with Nathan Ramesh 8 Hyper-Dimensional Geometry 8 IOL 2016 8 Many Cells Separating Points 9 Period Three Implies Chaos 9 Problem Solving: Tetrahedra 9 The Brauer Group 9 The BSD conjecture 10 The Cayley{Hamilton Theorem 10 The \Free Will" Theorem 10 The Yoneda Lemma 10 Twisty Puzzles are Easy 11 Wedderburn's Theorem 11 Wythoff's Game 11 1:10 Classes 11 Big Numbers 11 Graph Polynomials 12 Hard Problems That Are Almost Easy 12 Hyperbolic Geometry 12 Latin Squares and Finite Geometries 13 1 MC2016 ◦ W5 ◦ Classes 2 Multiplicative Functions 13 Permuting Conditionally Convergent Series 13 The Cap Set Problem 13 2:10 Classes 14 Computer-Aided Design 14 Factoring with Elliptic Curves 14 Math and Literature 14 More Group Theory! 15 Paradoxes in Probability 15 The Hales{Jewett Theorem 15 9:10 Classes Building Groups out of Other Groups. ( , Don, Wednesday{Friday) In group theory, everybody learns how to take a group, and shrink it down by taking a quotient by a normal subgroup|but what they don't tell you is that you can totally go the other direction. -
Some Spectral and Quasi-Spectral Characterizations of Distance-Regular Graphs
Some spectral and quasi-spectral characterizations of distance-regular graphs A. Abiada;b, E.R. van Dama, M.A. Fiolc aTilburg University, Dept. of Econometrics and O.R. Tilburg, The Netherlands [email protected] bMaastricht University, Dept. of Quantitative Economics Maastricht, The Netherlands [email protected] cUniversitat Polit`ecnicade Catalunya, Dept. de Matem`atiques Barcelona Graduate School of Mathematics, Barcelona, Catalonia [email protected] Abstract In this paper we consider the concept of preintersection numbers of a graph. These numbers are determined by the spectrum of the adjacency matrix of the graph, and generalize the intersection numbers of a distance-regular graph. By using the prein- tersection numbers we give some new spectral and quasi-spectral characterizations of distance-regularity, in particular for graphs with large girth or large odd-girth. Mathematics Subject Classifications: 05E30, 05C50. Keywords: Distance-regular graph; Eigenvalues; Girth; Odd-girth; Preintersection numbers. 1 Introduction A central issue in spectral graph theory is to question whether or not a graph is uniquely determined by its spectrum, see the surveys of Van Dam and Haemers [12, 13]. In partic- arXiv:1404.3973v4 [math.CO] 19 Apr 2016 ular, much attention has been paid to give spectral and quasi-spectral characterizations of distance-regularity. Contributions in this area are due to Brouwer and Haemers [3], Van Dam and Haemers [11], Van Dam, Haemers, Koolen, and Spence [15], Haemers [22], and Huang and Liu [24], among others. In this paper, we will give new spectral and quasi-spectral characterizations of distance- regularity of a graph G without requiring, as it is common in this area of research, that: • G is cospectral with a distance-regular graph Γ, where 1 2 • Γ has intersection numbers, or other combinatorial parameters that satisfy certain properties. -
WEEK 5 CLASS PROPOSALS, MATHCAMP 2018 Contents
WEEK 5 CLASS PROPOSALS, MATHCAMP 2018 Abstract. We have a lot of fun class proposals for Week 5! Take a read through these proposals, and then let us know which ones you would like us to schedule for Week 5 by submitting your preferences on the appsys appsys.mathcamp.org. We'll keep voting open until sign-in on Wednesday evening. Please only vote for classes that you would attend if offered. Thanks for helping us create the schedule! Contents Aaron's Classes 3 Braid groups and the fundamental group of configuration space 3 Counting points over finite fields 4 Dimensional Analysis 4 Finite Fields 4 Math is Applied Physics 4 Riemann-Roching out on the projective line 4 The Art of Live-TeXing 4 The dimension formula for modular forms via the moduli stack of elliptic curves 5 Aaron, Vivian's Classes 5 Galois Theory and Number Theory 5 Ania, Jessica's Classes 5 Cycles in permutations 5 Apurva's Classes 6 Galois Correspondence of Covering Spaces 6 MP3 6= JPEG 6 The Quantum Spring 6 There isn't enough Homological Algebra in the world 6 Would I ever Lie Group to you? 6 Ben Dees's Classes 6 Bairely Sensible 6 Finite Field Fourier Fun 7 What is a \Sylow" anyways? 7 Yes, you can trisect angles 7 Brian Reinhart's Classes 8 A Slice of PIE 8 Dyusha, Michelle's Classes 8 Curse of Dimensionality 8 J-Lo's Classes 9 Axiomatic Music Theory part 2: Rhythm 9 Lattices 9 Minus Choice, Still Paradoxes 9 The Borsuk Problem 9 The Music of Zeta 10 Yes, you can solve the Quintic 10 Jeff's Classes 10 1 MC2018 ◦ W5 ◦ Classes 2 Combinatorial Topology 10 Jeff's Favorite Pictures -
Devising a Framework for Efficient and Accurate Matchmaking and Real-Time Web Communication
Dartmouth College Dartmouth Digital Commons Dartmouth College Undergraduate Theses Theses and Dissertations 6-1-2016 Devising a Framework for Efficient and Accurate Matchmaking and Real-time Web Communication Charles Li Dartmouth College Follow this and additional works at: https://digitalcommons.dartmouth.edu/senior_theses Part of the Computer Sciences Commons Recommended Citation Li, Charles, "Devising a Framework for Efficient and Accurate Matchmaking and Real-time Web Communication" (2016). Dartmouth College Undergraduate Theses. 106. https://digitalcommons.dartmouth.edu/senior_theses/106 This Thesis (Undergraduate) is brought to you for free and open access by the Theses and Dissertations at Dartmouth Digital Commons. It has been accepted for inclusion in Dartmouth College Undergraduate Theses by an authorized administrator of Dartmouth Digital Commons. For more information, please contact [email protected]. Devising a framework for efficient and accurate matchmaking and real-time web communication Charles Li Department of Computer Science Dartmouth College Hanover, NH [email protected] Abstract—Many modern applications have a great need for propose and evaluate original matchmaking algorithms, and matchmaking and real-time web communication. This paper first also discuss and evaluate implementations of real-time explores and details the specifics of original algorithms for communication using existing web protocols. effective matchmaking, and then proceeds to dive into implementations of real-time communication between different clients across the web. Finally, it discusses how to apply the II. PRIOR WORK AND RELEVANT TECHNOLOGIES techniques discussed in the paper in practice, and provides samples based on the framework. A. Matchmaking: No Stable Matching Exists Consider a pool of users. What does matchmaking entail? It Keywords—matchmaking; real-time; web could be the task of finding, for each user, the best compatriot or opponent in the pool to match with, given the user’s set of I. -
Cheating to Get Better Roommates in a Random Stable Matching
Dartmouth College Dartmouth Digital Commons Computer Science Technical Reports Computer Science 12-1-2006 Cheating to Get Better Roommates in a Random Stable Matching Chien-Chung Huang Dartmouth College Follow this and additional works at: https://digitalcommons.dartmouth.edu/cs_tr Part of the Computer Sciences Commons Dartmouth Digital Commons Citation Huang, Chien-Chung, "Cheating to Get Better Roommates in a Random Stable Matching" (2006). Computer Science Technical Report TR2006-582. https://digitalcommons.dartmouth.edu/cs_tr/290 This Technical Report is brought to you for free and open access by the Computer Science at Dartmouth Digital Commons. It has been accepted for inclusion in Computer Science Technical Reports by an authorized administrator of Dartmouth Digital Commons. For more information, please contact [email protected]. Cheating to Get Better Roommates in a Random Stable Matching Chien-Chung Huang Technical Report 2006-582 Dartmouth College Sudikoff Lab 6211 for Computer Science Hanover, NH 03755, USA [email protected] Abstract This paper addresses strategies for the stable roommates problem, assuming that a stable matching is chosen at random. We investigate how a cheating man should permute his preference list so that he has a higher-ranking roommate probabilistically. In the first part of the paper, we identify a necessary condition for creating a new stable roommate for the cheating man. This condition precludes any possibility of his getting a new roommate ranking higher than all his stable room- mates when everyone is truthful. Generalizing to the case that multiple men collude, we derive another impossibility result: given any stable matching in which a subset of men get their best possible roommates, they cannot cheat to create a new stable matching in which they all get strictly better roommates than in the given matching. -
PDF Reference
NetworkX Reference Release 1.0 Aric Hagberg, Dan Schult, Pieter Swart January 08, 2010 CONTENTS 1 Introduction 1 1.1 Who uses NetworkX?..........................................1 1.2 The Python programming language...................................1 1.3 Free software...............................................1 1.4 Goals...................................................1 1.5 History..................................................2 2 Overview 3 2.1 NetworkX Basics.............................................3 2.2 Nodes and Edges.............................................4 3 Graph types 9 3.1 Which graph class should I use?.....................................9 3.2 Basic graph types.............................................9 4 Operators 129 4.1 Graph Manipulation........................................... 129 4.2 Node Relabeling............................................. 134 4.3 Freezing................................................. 135 5 Algorithms 137 5.1 Boundary................................................. 137 5.2 Centrality................................................. 138 5.3 Clique.................................................. 142 5.4 Clustering................................................ 145 5.5 Cores................................................... 147 5.6 Matching................................................. 148 5.7 Isomorphism............................................... 148 5.8 PageRank................................................. 161 5.9 HITS.................................................. -
Online Assessment of Graph Theory
ONLINE ASSESSMENT OF GRAPH THEORY A thesis submitted for the degree of Doctor of Philosophy By Justin Dale Hatt College of Engineering, Design and Physical Sciences Brunel University August 2016 Abstract The objective of this thesis is to establish whether or not online, objective questions in elementary graph theory can be written in a way that exploits the medium of computer-aided assessment. This required the identification and resolution of question design and programming issues. The resulting questions were trialled to give an extensive set of answer files which were analysed to identify whether computer delivery affected the questions in any adverse ways and, if so, to identify practical ways round these issues. A library of questions spanning commonly-taught topics in elementary graph theory has been designed, programmed and added to the graph theory topic within an online assessment and learning tool used at Brunel University called Mathletics. Distracters coded into the questions are based on errors students are likely to make, partially evidenced by final examination scripts. Questions were provided to students in Discrete Mathematics modules with an extensive collection of results compiled for analysis. Questions designed for use in practice environments were trialled on students from 2007 – 2008 and then from 2008 to 2014 inclusive under separate testing conditions. Particular focus is made on the relationship of facility and discrimination between comparable questions during this period. Data is grouped between topic and also year group for the 2008 – 2014 tests, namely 2008 to 2011 and 2011 to 2014, so that it may then be determined what factors, if any, had an effect on the overall results for these questions.