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UID:www.tcs.tifr.res.in/event/951
DTSTAMP:20230914T125944Z
SUMMARY:k-means clustering\, stability and outliers
DESCRIPTION:Speaker: Amit Deshpande (Microsoft Research India\nBangalore)\n
 \nAbstract: \nAbstract: k-means is a popular clustering objective that is 
 NP-hard in theory but often optimized efficiently in practice. Sampling-ba
 sed algorithms such as k-means++ and approximation schemes give provable a
 pproximation guarantees for the worst-case instances of k-means. In this t
 alk\, we will discuss new results on how these algorithms perform for stab
 le instances and in the presence of outliers. Based on joint works with (a
 ) Anand Louis\, Apoorv Vikram Singh (IISc) and (b) Praneeth Kacham (IIT De
 lhi)\, Rameshwar Pratap (IIIT Bangalore).\n
URL:https://www.tcs.tifr.res.in/web/events/951
DTSTART;TZID=Asia/Kolkata:20190319T113000
DTEND;TZID=Asia/Kolkata:20190319T123000
LOCATION:A-201 (STCS Seminar Room)
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