BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Drupal iCal API//EN X-WR-CALNAME:Events items teaser X-WR-TIMEZONE:America/Toronto BEGIN:VTIMEZONE TZID:America/Toronto X-LIC-LOCATION:America/Toronto BEGIN:DAYLIGHT TZNAME:EDT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 DTSTART:20220313T070000 END:DAYLIGHT BEGIN:STANDARD TZNAME:EST TZOFFSETFROM:-0400 TZOFFSETTO:-0500 DTSTART:20221106T060000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:6830f7c42f620 DTSTART;TZID=America/Toronto:20221125T120000 SEQUENCE:0 TRANSP:TRANSPARENT DTEND;TZID=America/Toronto:20221125T120000 URL:/combinatorics-and-optimization/events/combinatoria l-optimization-reading-group-ian-dehaan SUMMARY:Combinatorial Optimization Reading Group - Ian DeHaan CLASS:PUBLIC DESCRIPTION:Summary \n\nTitle: Greedy algorithm for stochastic matching is a 2-approximatio\n\nSpeaker:\n Ian DeHaan\n\nAffiliation:\n University of À¶Ý®ÊÓÆµ\n\nLocation:\n MC 6029 or contact Rian Neogi for Zoom link\n\n Abstract: We will discuss the greedy algorithm for the stochastic\nmatchin g problem. In this problem\, we are given an undirected graph\nwhere each edge is assigned a probability p_e in [0\, 1] and each\nvertex is assigned a patience t_v in Z+. We begin each step by probing\nan edge e which is n ot adjacent to any edges in our matching. The\nprobe will succeed with pro bability p_e\, and if it does\, we add e to\nour matching. Otherwise\, we may not probe e again. We also may not\nprobe edges adjacent to a vertex v more than t_v times. The goal is to\nmaximize the number of edges we add to our matching. \n DTSTAMP:20250523T223340Z END:VEVENT END:VCALENDAR