BEGIN:VCALENDAR
VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:Asia/Hong_Kong
BEGIN:STANDARD
DTSTART:19791021T023000
TZOFFSETFROM:+0900
TZOFFSETTO:+0800
TZNAME:HKT
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20181108T032444Z
UID:F9474340-BBCE-4C19-9961-6B6BCCD5A271
DTSTART;TZID=Asia/Hong_Kong:20180727T110000
DTEND;TZID=Asia/Hong_Kong:20180727T121000
DESCRIPTION:FPGA implementations of machine learning algorithms have been s
 hown to be extremely efficient when the problem fits entirely on the FPGA 
 but it remains a challenge to scale to problems of interest to industry. I
 n this talk\, our recent research on how to increase the capacity of exist
 ing approaches will be described.\n\nSpeaker(s): Prof. Philip Leong\, \n\n
 City University of HK\, G6302\, 6/F\, Green Zone\, Yeung Kin Man Academic 
 Building\, Hong Kong\, Guangdong\, China
LOCATION:City University of HK\, G6302\, 6/F\, Green Zone\, Yeung Kin Man A
 cademic Building\, Hong Kong\, Guangdong\, China
ORGANIZER:e.cheung@ieee.org
SEQUENCE:0
SUMMARY:Large-Scale FPGA implementations of Machine Learning Algorithms
URL;VALUE=URI:https://events.vtools.ieee.org/m/181465
X-ALT-DESC:Description: <br /><p>FPGA implementations of machine learning a
 lgorithms have been shown to be extremely efficient when the problem fits 
 entirely on the FPGA but it remains a challenge to scale to problems of in
 terest to industry. In this talk\, our recent research on how to increase 
 the capacity of existing approaches will be described.</p>
END:VEVENT
END:VCALENDAR