LarremoreShewRestrepov2.dvi

First Page		Document Content
Date: 2012-12-06 14:42:04 Network theory Mathematics Discrete mathematics Applied mathematics Assortativity Complex network Scale-free network Artificial neural network Assortative mixing Degree distribution		LarremoreShewRestrepov2.dvi Add to Reading List Source URL: danlarremore.com Download Document from Source Website File Size: 203,63 KB Share Document on Facebook

	Understanding Resolution Proofs through Herbrand’s Theorem‹ Stefan Hetzl1 , Tomer Libal2 , Martin Riener3 , and Mikheil Rukhaia4 1 Institute of Discrete Mathematics and Geometry, Vienna University of Technology DocID: 1xTCQ - View Document
	Using Alloy in a Language Lab Approach to Introductory Discrete Mathematics Charles Wallace Michigan Technological University In collaboration with Laura Brown, Adam Feltz DocID: 1xTvc - View Document
	Applicable Analysis and Discrete Mathematics available online at http://pefmath.etf.bg.ac.yu Appl. Anal. Discrete Math), 322–337. doi:AADM100425018H DocID: 1vmuF - View Document
	Discrete Mathematics and Theoretical Computer Science DMTCS vol. (subm.), by the authors, 1–1 A lower bound for approximating the grundy number DocID: 1vkug - View Document
	Hausdorﬀ Center for Mathematics, Summer School (May 9–13, 2016) Problems for “Discrete Convex Analysis” (by Kazuo Murota) Problem 1. Prove that a function f : Z2 → R defined by f (x1 , x2 ) = φ(x1 − x2 ) is DocID: 1vjVY - View Document