Hyperfinite graphs and combinatorial optimization László Lovász

Slides:



Advertisements
Similar presentations
Routing Complexity of Faulty Networks Omer Angel Itai Benjamini Eran Ofek Udi Wieder The Weizmann Institute of Science.
Advertisements

Great Theoretical Ideas in Computer Science
1 Decomposing Hypergraphs with Hypertrees Raphael Yuster University of Haifa - Oranim.
Great Theoretical Ideas in Computer Science for Some.
Graph Isomorphism Algorithms and networks. Graph Isomorphism 2 Today Graph isomorphism: definition Complexity: isomorphism completeness The refinement.
Nonlinear methods in discrete optimization László Lovász Eötvös Loránd University, Budapest
Combinatorial Algorithms
Christian Sohler | Every Property of Hyperfinite Graphs is Testable Ilan Newman and Christian Sohler.
Random Walks Ben Hescott CS591a1 November 18, 2002.
On the Hardness of Graph Isomorphism Jacobo Tor á n SIAM J. Comput. Vol 33, p , Presenter: Qingwu Yang April, 2006.
EXPANDER GRAPHS Properties & Applications. Things to cover ! Definitions Properties Combinatorial, Spectral properties Constructions “Explicit” constructions.
Ramanujan Graphs of Every Degree Adam Marcus (Crisply, Yale) Daniel Spielman (Yale) Nikhil Srivastava (MSR India)
MATH 310, FALL 2003 (Combinatorial Problem Solving) Lecture 10, Monday, September 22.
THE EXTENSION OF COLLISION AND AVALANCHE EFFECT TO k-ARY SEQUENCES Viktória Tóth Eötvös Loránd University, Budapest Department of Algebra and Number Theory,
Algorithms on negatively curved spaces James R. Lee University of Washington Robert Krauthgamer IBM Research (Almaden) TexPoint fonts used in EMF. Read.
Which graphs are extremal? László Lovász Eötvös Loránd University, Budapest Joint work with Balázs Szegedy.
Graph Coalition Structure Generation Maria Polukarov University of Southampton Joint work with Tom Voice and Nick Jennings HUJI, 25 th September 2011.
Graph limit theory: Algorithms László Lovász Eötvös Loránd University, Budapest May
July The Mathematical Challenge of Large Networks László Lovász Eötvös Loránd University, Budapest
Algorithms on large graphs László Lovász Eötvös Loránd University, Budapest May
Edge-disjoint induced subgraphs with given minimum degree Raphael Yuster 2012.
Graph limit theory: an overview László Lovász Eötvös Loránd University, Budapest IAS, Princeton June
October Large networks: a new language for science László Lovász Eötvös Loránd University, Budapest
Convergent sequences of sparse graphs (status report) László Lovász Eötvös University, Budapest.
Optimization in very large graphs László Lovász Eötvös Loránd University, Budapest December
The countable character of uncountable graphs François Laviolette Barbados 2003.
Local and global convergence in bounded degree graphs László Lovász Eötvös Loránd University, Budapest Joint work with Christian Borgs, Jennifer Chayes.
The mathematical challenge of large networks László Lovász Eötvös Loránd University, Budapest Joint work with Christian Borgs, Jennifer Chayes, Balázs.
Regularity partitions and the topology of graphons László Lovász Eötvös Loránd University, Budapest Joint work Balázs Szegedy August
1 Quasi-randomness is determined by the distribution of copies of a graph in equicardinal large sets Raphael Yuster University of Haifa.
State space representations and search strategies - 2 Spring 2007, Juris Vīksna.
New algorithms for Disjoint Paths and Routing Problems
Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós.
Graphs, Vectors, and Matrices Daniel A. Spielman Yale University AMS Josiah Willard Gibbs Lecture January 6, 2016.
Graph algebras and graph limits László Lovász
January 2016 Spectra of graphs and geometric representations László Lovász Hungarian Academy of Sciences Eötvös Loránd University
Nondeterministic property testing László Lovász Katalin Vesztergombi.
Dense graph limit theory: Extremal graph theory László Lovász Eötvös Loránd University, Budapest May
Introduction Wireless Ad-Hoc Network  Set of transceivers communicating by radio.
Primbs, MS&E345 1 Measure Theory in a Lecture. Primbs, MS&E345 2 Perspective  -Algebras Measurable Functions Measure and Integration Radon-Nikodym Theorem.
Theory of Computational Complexity Probability and Computing Chapter Hikaru Inada Iwama and Ito lab M1.
Hyperfinite graphs and combinatorial optimization László Lovász
Review: Discrete Mathematics and Its Applications
Algorithms for Finding Distance-Edge-Colorings of Graphs
Hans Bodlaender, Marek Cygan and Stefan Kratsch
The countable character of uncountable graphs François Laviolette Barbados 2003.
Graph Theory and Algorithm 01
Great Theoretical Ideas in Computer Science
Algorithms and networks
Complexity of Expander-Based Reasoning and the Power of Monotone Proofs Sam Buss (UCSD), Valentine Kabanets (SFU), Antonina Kolokolova.
Discrete Mathematics for Computer Science
Graph limits and graph homomorphisms László Lovász Microsoft Research
Algorithms and networks
3.5 Minimum Cuts in Undirected Graphs
Department of Computer Science University of York
CSE838 Lecture notes copy right: Moon Jung Chung
Partitioning and decomposing graphs László Lovász
geometric representations of graphs
Introduction Wireless Ad-Hoc Network
Review: Discrete Mathematics and Its Applications
Around the Regularity Lemma
Miniconference on the Mathematics of Computation
Embedding Metrics into Geometric Spaces
Lecture 6: Counting triangles Dynamic graphs & sampling
Lecture 15: Least Square Regression Metric Embeddings
Warm Up – Tuesday Find the critical times for each vertex.
Distance-preserving Subgraphs of Interval Graphs
Eötvös Loránd Tudományegyetem, Budapest
Treewidth meets Planarity
Presentation transcript:

Hyperfinite graphs and combinatorial optimization László Lovász Hungarian Academy of Sciences and Eötvös Loránd University, Budapest January 2018

Don in Epidauros 1995 January 2018

Bounded degree ( D) Borel graph Graphing, definition Bounded degree ( D) Borel graph on standard probability space V (say [0,1]) with “double counting” condition: Extends to measure  on Borel subsets of V2. „edge measure” January 2018

„The notion of an algorithm is basic to Why graphings? „The notion of an algorithm is basic to all of computer programming, so we should begin with a careful analysis of this concept.” Donald Knuth January 2018

Find a perfect matching in G. Why graphings? Find a perfect matching in G. distributed algorithm: Nguyen and Onak January 2018

distributed algorithms Why graphings? distributed algorithms local algorithms (on bounded degree graphs) January 2018

distributed algorithms Why graphings? distributed algorithms local algorithms (on bounded degree graphs) property testing (on bounded degree graphs) January 2018

distributed algorithms Why graphings? distributed algorithms local algorithms (on bounded degree graphs) property testing (on bounded degree graphs) local algorithms on graphings The infinite is a good approximation of the large finite. January 2018

Why graphings? Ergodic theory Finitely generated groups Limits of convergent graphs sequences with bounded degree January 2018

Graphing, examples January 2018

Graphing, examples unit circumference  irrational components: 2-way infinite paths January 2018

, irrational, lin. indep 1x1 torus , irrational Graphing, examples unit circumference , irrational, lin. indep   1x1 torus , irrational components: grids   components: grids January 2018

Penrose tilings rhombic icosahedron de Bruijn - Bárász January 2018

Local equivalence, definition xV  Gx: component of x uniform random x  Gx: random connected rooted (countable) graph unimodular random network Benjamini - Schramm January 2018

Local equivalence, definition xV  Gx: component of x G1, G2 locally equivalent: for random uniform xV, distributions of (G1)x and (G2)x are the same January 2018

Local isomorphism, definition  : V(G1)  V(G2) local isomorphism: measure preserving and (x) isomorphism between (G1)x and (G2)(x) Existence of local isomorphism proves local equivalence. January 2018

Local isomorphism, example   (x,y)  x+y mod 1    components: grids components: grids January 2018

G1 and G2 are locally equivalent  Local equivalence G1 and G2 are locally equivalent  G and local isomorphisms GG1, GG2. G1 G2 G January 2018

Graph partition problem k-edge-separator: TE(G), component of G-T has  k nodes Graphing G hyperfinite: sepk(G)0 (k) January 2018

Hyperfinite graphings, examples   Diophantine approximation   January 2018

Hyperfinite graph families Family G of finite graphs is hyperfinite: Hyperfinite: paths, trees, planar graphs, every non-trivial minor-closed property Non-hyperfinite: expanders January 2018

Every graph property is testable in any family of hyperfinite graphs. Hyperfinite graph families Every graph property is testable in any family of hyperfinite graphs. Many graph properties are polynomial time testable for graphs with bounded tree-width. Newman – Sohler (Benjamini-Schramm-Shapira, Elek) January 2018

{Gn} is hyperfinite  G is hyperfinite Hyperfinite graph sequences If Gn  G locally, then {Gn} is hyperfinite  G is hyperfinite Schramm (Benjamini-Shapira-Schramm) January 2018

? Hyperfinite graphings If G1 and G2 are locally equivalent, then G1 is hyperfinite  G2 is hyperfinite G1 G2 G ? January 2018

Local isomorphism forward Diophantine approximation  (x,y)  x+y mod 1     January 2018

Pushing forward and pulling back measure preserving subset linear relaxation measure January 2018

Fractional graph partition problem T: optimal k-edge-separator January 2018

Fractional graph partition problem probability distribution „marginal” uniform expected expansion January 2018

Fractional graph/graphing partition problem Define Can be defined for graphings  probability distribution on Rk with uniform marginal no dependence on k January 2018

Hyperfinite graphings If G1 and G2 are locally equivalent, then G1 is hyperfinite  G2 is hyperfinite G1 G2 G January 2018

Algorithm: For j=1,2,..., select Y1,Y2,...k so that Proof sketch Algorithm: For j=1,2,..., select Y1,Y2,...k so that Yj is the minimizer of Output: X=Y1 Y2 ... On a graphing: no uncountable sequence of steps! Phases... January 2018

Fractional separation duality If G1 and G2 are locally equivalent, then G1 G2 easy ? Duality! January 2018

Fractional separation duality Hahn-Banach + Riesz Representation January 2018

Fractional separation duality January 2018

Thanks, that’s all! January 2018