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DTSTART:20180311T070000
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DTSTART:20171105T060000
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UID:69b12d1e0819b
DTSTART;TZID=America/Toronto:20180420T093000
SEQUENCE:0
TRANSP:TRANSPARENT
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URL:https://uwaterloo.ca/artificial-intelligence-group/events/masters-thesi
 s-presentation-experimental-analysis-multi
LOCATION:DC - William G. Davis Computer Research Centre 200 University Aven
 ue West 2585 Waterloo ON N2L 3G1 Canada
SUMMARY:Master's Thesis Presentation: An Experimental Analysis of\nMulti-Pe
 rspective Convolutional Neural Networks
CLASS:PUBLIC
DESCRIPTION:Speaker: Zhucheng Tu\, Master's Candidate\n\nModelling the simi
 larity of two sentences is an important problem in\nnatural language proce
 ssing and information retrieval\, with\napplications in tasks such as para
 phrase identification and answer\nselection in question answering. The Mul
 ti-Perspective Convolutional\nNeural Network (MP-CNN) is a model that impr
 oved previous\nstate-of-the-art models in 2015 and has remained a popular 
 model for\nsentence similarity tasks. However\, until now\, there has not 
 been a\nrigorous study of how the model actually achieves competitive\nacc
 uracy. 
DTSTAMP:20260311T085142Z
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