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1
Intro
2
Greedy Matching
3
Oblivious Matching Goel and Tripathi 2012
4
Understanding of MRG
5
Modified Randomized Greedy (MRG)
6
Our Algorithm and Results
7
Weighted Oblivious Matching
8
Perturbed Greedy vs RDO
9
Analysis
10
Roadmap
11
Basic Lower Bound
12
Extra Gain: Warm-up Case
13
Alternating Path
14
Improved Lower Bound: Bipartite
15
Bad case in General graph
16
A compensation Idea
17
Define "Victim"
18
v Is Not A Victim?
19
Extra gain: General
Description:
Explore the intricacies of randomized greedy matching algorithms in this 23-minute conference talk presented at the Association for Computing Machinery (ACM). Delve into the evolution of greedy matching techniques, starting from oblivious matching and progressing to Modified Randomized Greedy (MRG) algorithms. Examine the speaker's novel approach and results, including insights on weighted oblivious matching and the comparison between Perturbed Greedy and RDO methods. Follow the analysis roadmap, covering basic lower bounds, extra gain scenarios, and the concept of alternating paths. Investigate improved lower bounds in bipartite graphs and challenging cases in general graphs. Gain a deeper understanding of compensation ideas, the definition of "victims" in the algorithm, and extra gain considerations for general graph scenarios.

Towards a Better Understanding of Randomized Greedy Matching

Association for Computing Machinery (ACM)
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