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DTSTART:20190310T070000
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DTSTART;TZID=America/Toronto:20190529T113000
SEQUENCE:0
TRANSP:TRANSPARENT
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URL:https://uwaterloo.ca/artificial-intelligence-group/events/phd-defence-t
 heoretical-foundations-efficient-clustering
LOCATION:DC - William G. Davis Computer Research Centre 200 University Aven
 ue West 2310 Waterloo ON N2L 3G1 Canada
SUMMARY:PhD Defence: Theoretical Foundations for Efficient Clustering
CLASS:PUBLIC
DESCRIPTION:SHRINU KUSHAGRA\, PHD CANDIDATE\n_David R. Cheriton School of C
 omputer Science_\n\nClustering aims to group together data instances which
  are similar\nwhile simultaneously separating the dissimilar instances. Th
 e task of\nclustering is challenging due to many factors. The most well-st
 udied\nis the high computational cost. The clustering task can be viewed a
 s\nan optimization problem where the goal is to minimize a certain cost\nf
 unction (like k-means cost or k-median cost). Not only are the\nminimizati
 on problems NP-Hard but often also NP-Hard to approximate\n(within a const
 ant factor). There are two other major issues in\nclustering\, namely unde
 r-specificity and noise-robustness. 
DTSTAMP:20260315T123834Z
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