PPT-Algorithms on large graphs

Author : calandra-battersby | Published Date : 2016-04-08

L á szl ó Lov á sz Eötvös Lor ánd University Budapest May 2013 1 Happy Birthday Ravi May 2013 2 Cut norm of matrix A n x n The Weak Regularity Lemma

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Algorithms on large graphs: Transcript


L á szl ó Lov á sz Eötvös Lor ánd University Budapest May 2013 1 Happy Birthday Ravi May 2013 2 Cut norm of matrix A n x n The Weak Regularity Lemma. Carla . Binucci. , Emilio Di Giacomo, . Walter Didimo, Fabrizio Montecchiani, Maurizio . Patrignani. , . Ioannis. G. . Tollis. Fan-planar drawings. Fan-planar drawings. Given a graph G, a . fan-planar drawing . Angelika Steger. (j. oint. . work. . with. . Konstantinos . Panagiotou. , SODA‘11. ) . . TexPoint fonts used in EMF. . Read the TexPoint manual before you delete this box.: . A. A. A. A. A. Random Graphs . Learning Goals:. Graphs of the Cosecant, Secant, and Cotangent Functions. Graph transformations . When you think about the . csc. , sec, and cot graphs what do you think about?. Graph of the Cosecant Function. Masaru . Kamada. Tokyo . University of . Science. Graph Theory Conference. i. n honor of Yoshimi . Egawa. on the occasion his 60. th. birthday. September 10-14, 2013. In this talk, all graphs are finite, undirected and allowed multiple edges without loops.. Misleading Graphs. Good . graphs are extremely powerful tools for displaying large quantities . of complex . data; they help turn the realms of information available today . into knowledge. . But, unfortunately, some graphs deceive or mislead. This . Minors, . Bidimensionality. ,. & Decomposition. r. r. Erik Demaine. MIT. Goals. How far . beyond planar graphs . can we go?. Graphs excluding. a fixed minor. Powers thereof. Build . general approximation frameworks . Sometimes, two graphs have exactly the same form, in the sense that there is a one-to-one correspondence between their vertex sets that preserves edges. In such a case, we say that the two graphs are . Daniel A. Spielman. Yale University. AMS Josiah Willard Gibbs Lecture. January . 6. , 2016 . From Applied to Pure Mathematics. Algebraic and Spectral Graph Theory. . . Sparsification. :. a. pproximating graphs by graphs with fewer edges. The type of graph you draw depends on the types of observations you make. Bar Graph. Line Graph. Pie Graph. Bar and Column Graphs. Bar and column graphs. Some observations fall into . discrete. groupings. The vertical scale is too big or too small, or skips numbers, or doesn’t start at zero.. The graph isn’t labeled properly.. Data is left out.. But some real life misleading graphs go above and beyond the classic types. Some are intended to mislead, others are intended to shock. And in some cases, well-meaning individuals just got it all plain wrong. These are some of my favorite recent-history misleading graphs from real life.. Planar graphs. 2. Planar graphs. Can be drawn on the plane without crossings. Plane graph: planar graph, given together with an embedding in the plane. Many applications…. Questions:. Testing if a graph is planar. Richard Peng. Georgia Tech. In collaboration with. Michael B. Cohen. Jon . Kelner. John Peebles. Aaron . Sidford. Adrian . Vladu. Anup. . B. Rao. Rasmus. . Kyng. Outline. Graphs and . Lx. = . b. G . 10 Bat Algorithms Xin-She Yang, Nature-Inspired Optimization Algorithms, Elsevier, 2014 The bat algorithm (BA) is a bio-inspired algorithm developed by Xin-She Yang in 2010. 10.1 Echolocation of Bats Matching Algorithms and Networks Algorithms and Networks: Matching 2 This lecture Matching: problem statement and applications Bipartite matching (recap) Matching in arbitrary undirected graphs: Edmonds algorithm

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