BEGIN:VCALENDAR VERSION:2.0 PRODID:-//UC Irvine//CML Seminars//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:Revisiting FastMap: New Applications X-WR-TIMEZONE:America/Los_Angeles BEGIN:VTIMEZONE TZID:America/Los_Angeles BEGIN:DAYLIGHT TZOFFSETFROM:-0800 TZOFFSETTO:-0700 TZNAME:PDT DTSTART:20070311T020000 RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0700 TZOFFSETTO:-0800 TZNAME:PST DTSTART:20071104T020000 RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:2025-01-27-satish-kumar-thittamaranahalli@cml.ics.uci.edu DTSTAMP:20250127T000000Z SEQUENCE:57690 DTSTART;TZID=America/Los_Angeles:20250127T130000 DTEND;TZID=America/Los_Angeles:20250127T140000 SUMMARY:[CML Seminar] Satish Kumar Thittamaranahalli: Revisiting FastMap: N ew Applications LOCATION:Donald Bren Hall 4011 DESCRIPTION:Satish Kumar Thittamaranahalli\, Research Associate Professor\, Department of Computer Science\, University of Southern California\n\nTit le: Revisiting FastMap: New Applications\n\nAbstract: FastMap was first in troduced in the Data Mining community for generating Euclidean embeddings of complex objects. In this talk\, I will first generalize FastMap to gene rate Euclidean embeddings of graphs in near-linear time: The pairwise Eucl idean distances approximate a desired graph-based distance function on the vertices. I will then apply the graph version of FastMap to efficiently s olve various graph-theoretic problems of significant interest in AI: inclu ding shortest-path computations\, facility location\, top-K centrality com putations\, and community detection and block modeling. I will also presen t a novel learning framework\, called FastMapSVM\, by combining FastMap an d Support Vector Machines. I will then apply FastMapSVM to predict the sat isfiability of Constraint Satisfaction Problems and to classify seismogram s in Earthquake Science.\n\nhttps://cml.ics.uci.edu/seminars/2025-01-27-sa tish-kumar-thittamaranahalli X-ALT-DESC;FMTTYPE=text/html:Satish Kumar Thittamaranahalli< /b>\, Research Associate Professor\, Department of Computer Science\, Univ ersity of Southern California

Title: Revisiting FastMap: New Applications

Abstract: FastMap was first introduced in the Data Mining community for generating Euclidean embeddings of complex objec ts. In this talk\, I will first generalize FastMap to generate Euclidean e mbeddings of graphs in near-linear time: The pairwise Euclidean distances approximate a desired graph-based distance function on the vertices. I wil l then apply the graph version of FastMap to efficiently solve various gra ph-theoretic problems of significant interest in AI: including shortest-pa th computations\, facility location\, top-K centrality computations\, and community detection and block modeling. I will also present a novel learni ng framework\, called FastMapSVM\, by combining FastMap and Support Vector Machines. I will then apply FastMapSVM to predict the satisfiability of C onstraint Satisfaction Problems and to classify seismograms in Earthquake Science.

https://cml.ics.uci.edu/seminars/2025-01-27-sat ish-kumar-thittamaranahalli URL:https://cml.ics.uci.edu/seminars/2025-01-27-satish-kumar-thittamaranaha lli END:VEVENT END:VCALENDAR