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DTSTART:20180311T070000
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DTSTART;TZID=America/Toronto:20180921T133000
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URL:https://uwaterloo.ca/computer-science/events/masters-thesis-presentatio
 n-scientific-computation
LOCATION:DC - William G. Davis Computer Research Centre 200 University Aven
 ue West 2310 Waterloo ON N2L 3G1 Canada
SUMMARY:Master’s Thesis Presentation • Scientific Computation —\nBidi
 rectional Learning in Recurrent Neural Networks Using Equilibrium\nPropaga
 tion
CLASS:PUBLIC
DESCRIPTION:AHMED KHAN\, MASTER’S CANDIDATE\nDavid R. Cheriton School of 
 Computer Science\n\nNeurobiologically-plausible learning algorithms for re
 current neural\nnetworks that can perform supervised learning are a neglec
 ted area of\nstudy. Equilibrium propagation is a recent synthesis of sever
 al ideas\nin biological and artificial neural network research that uses a
 \ncontinuous-time\, energy-based neural model with a local learning rule.\
 nHowever\, despite dealing with recurrent networks\, equilibrium\npropagat
 ion has only been applied to discriminative categorization\ntasks.
DTSTAMP:20260410T164941Z
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