Local Graph Clustering

Tuesday, July 30, 2019 11:00 am - 11:00 am EDT (GMT -04:00)

ProfessorÌýKimon Fountoulakis,ÌýSchool of Computer Science
University of À¶Ý®ÊÓÆµ

Abstract:Ìý

Graphs, long popular in computer science and discrete mathematics, have received renewed interest because they provide a useful way to model many types of relational data. In biology, e.g., graphs are routinely used to generate hypotheses for experimental validation; in neuroscience, they are used to study the networks and circuits in the brain; and in social networks, they are used to find common behaviors of users. These modern graph applications require the analysis of large graphs, and this can be computationally expensive. Graph algorithms have been developed to identify and interpret small-scale local structure in large-scale data without the requirement to access all the data. In this talk, we will discuss state-of-the-art local spectral- and flow-based algorithms that are specialized in finding small-scale clusters in large graphs without accessing the whole graph. We will discuss worst- and average-case theoretical results, we will present parallel versions of these algorithms for multi-core shared-memory hardware and we will demonstrate their empirical performance.Ìý


Bio:

KimonÌýFountoulakisÌýis anÌýAssistant Professor in the David R. Cheriton School of Computer ScienceÌýand a member of itsÌý.

Previously,ÌýKimonÌýwas aÌýpostdoctoral fellow and Principal Investigator atÌýUniversity of California Berkeley in theÌýDepartment of StatisticsÌýandÌýICSI. He workedÌýwithÌýMichaelÌýMahoney. Before that he completed a PhD in optimization atÌýUniversity of Edinburgh under the supervision ofÌýProfessorÌýJacekÌýGondzio.Ìý

Kimon'sÌýmost recent work focuses on large-scale optimization and its application to local graph clustering. He has also worked onÌýparallelizingÌýoptimization and local graphÌýanalyticsÌýalgorithms.

Kimon'sÌýpast work includes higher-order optimization methods for machine learning and signal processing problems.


Date and Time
Tuesday, 30 JulyÌý2019
11:00 AM - 12:00 PM

Location
DC 1302
University of À¶Ý®ÊÓÆµ

Light refreshments will be available.