[Theory] Re: [Theory Lunch] Konstantinos Ameranis, Wednesday 5/4 12:30pm-1:30pm, JCL 390.

[Adela DePavia]

Reminder: happening today in 1 hour
________________________________
From: Adela DePavia
Sent: Monday, May 2, 2022 10:53 AM
To: theory at mailman.cs.uchicago.edu <theory at mailman.cs.uchicago.edu>
Cc: Olga Medrano Martin del Campo <omedranomdelc at uchicago.edu>; Konstantinos Ameranis <kameranis at uchicago.edu>
Subject: [Theory Lunch] Konstantinos Ameranis, Wednesday 5/4 12:30pm-1:30pm, JCL 390.

Date: May 4th, Wednesday
Time: 12:30pm CT
Location: JCL 390

Speaker:  Konstantinos Ameranis

Title: Practical Nearly-Linear-Time Approximation Algorithms for Hybrid and Overlapping Graph Clustering

Zoom: [link<https://www.google.com/url?q=https%3A%2F%2Fuchicago.zoom.us%2Fj%2F96245648955%3Fpwd%3DeEJnV2xDSE1nZ3ErY2J3b0ZjK3dSUT09&sa=D&ust=1651938555712000&usg=AOvVaw1qcHB50_g0EIprlJDge879>]

Abstract: In many graph-clustering applications, overwhelming empirical evidence suggests that communities and clusters are naturally overlapping, calling for novel overlapping graph-partitioning algorithms ( OGP ). In this work, we introduce a framework based on two novel clustering objectives, which naturally extend the well-studied notion of conductance to overlapping clusters and to clusters with hybrid vertex- and edge-boundary structure. Our main algorithmic contributions are nearly-linear-time algorithms O(log n)-approximation algorithms for both these objectives. To this end, we show that the cut-matching framework of (Khandekar et al., 2014) can be extended to overlapping partitions and give novel cut-improvement primitives that perform a small number of s-t maximum flow computations over the instance graph to detect sparse overlapping partitions near an input partition. Crucially, we implement our approximation algorithm to produce both overlapping and hybrid partitions for large graphs, easily scaling to tens of millions of edges, and test our implementation on real-world datasets against other competitive baselines. Based on recent work with Lorenzo Orecchia.

COVID Policy: As per university policy, masking is not currently required for in-person attendance. Please note that we will have fully masked and social-distanced tables available to accommodate any attendees who would prefer such arrangements. Please contact us if you have any questions or feedback.

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