<?xml version="1.0" encoding="UTF-8"?><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcq="http://purl.org/dc/terms/"><records count="1" morepages="false" start="1" end="1"><record rownumber="1"><dc:product_type>Conference Paper</dc:product_type><dc:title>Convergence to Lexicographically Optimal Base in a (Contra)Polymatroid and Applications to Densest Subgraph and Tree Packing</dc:title><dc:creator>Harb, Elfarouk; Quanrud, Kent; Chekuri, Chandra</dc:creator><dc:corporate_author/><dc:editor>Gørtz, Inge Li; Farach-Colton, Martin; Puglisi, Simon J.; Herman, Grzegorz</dc:editor><dc:description>Boob et al. [Boob et al., 2020] described an iterative peeling algorithm called Greedy&amp;#43;&amp;#43; for the Densest Subgraph Problem (DSG) and conjectured that it converges to an optimum solution. Chekuri, Qaunrud and Torres [Chandra Chekuri et al., 2022] extended the algorithm to supermodular density problems (of which DSG is a special case) and proved that the resulting algorithm Super-Greedy&amp;#43;&amp;#43; (and hence also Greedy&amp;#43;&amp;#43;) converges. In this paper we revisit the convergence proof and provide a different perspective. This is done via a connection to Fujishige’s quadratic program for finding a lexicographically optimal base in a (contra) polymatroid [Satoru Fujishige, 1980], and a noisy version of the Frank-Wolfe method from convex optimization [Frank and Wolfe, 1956; Jaggi, 2013]. This yields a simpler convergence proof, and also shows a stronger property that Super-Greedy&amp;#43;&amp;#43; converges to the optimal dense decomposition vector, answering a question raised in Harb et al. [Harb et al., 2022]. A second contribution of the paper is to understand Thorup’s work on ideal tree packing and greedy tree packing [Thorup, 2007; Thorup, 2008] via the Frank-Wolfe algorithm applied to find a lexicographically optimum base in the graphic matroid. This yields a simpler and transparent proof. The two results appear disparate but are unified via Fujishige’s result and convex optimization.</dc:description><dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher><dc:date>2023-01-01</dc:date><dc:nsf_par_id>10500362</dc:nsf_par_id><dc:journal_name>31st Annual European Symposium on Algorithms, ESA 2023, September 4-6, 2023, Amsterdam, The Netherlands</dc:journal_name><dc:journal_volume/><dc:journal_issue/><dc:page_range_or_elocation/><dc:issn/><dc:isbn/><dc:doi>https://doi.org/10.4230/LIPICS.ESA.2023.56</dc:doi><dcq:identifierAwardId>2129816</dcq:identifierAwardId><dc:subject>Polymatroid</dc:subject><dc:subject>lexicographically optimum base</dc:subject><dc:subject>densest subgraph</dc:subject><dc:subject>tree packing</dc:subject><dc:subject>Networks → Network algorithms</dc:subject><dc:subject>Mathematics of computing → Graph algorithms</dc:subject><dc:version_number/><dc:location>Amsterdam, The Netherlands</dc:location><dc:rights/><dc:institution/><dc:sponsoring_org>National Science Foundation</dc:sponsoring_org></record></records></rdf:RDF>