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UID:69b64b8e06527
DTSTART;TZID=America/Toronto:20181214T150000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20181214T150000
URL:https://uwaterloo.ca/artificial-intelligence-group/events/phd-seminar-p
 rogressive-memory-banks-incremental-domain
LOCATION:DC - William G. Davis Computer Research Centre 200 University Aven
 ue West 2306C Waterloo ON N2L 3G1 Canada
SUMMARY:PhD Seminar: Progressive Memory Banks for Incremental Domain\nAdapt
 ation
CLASS:PUBLIC
DESCRIPTION:NABIHA ASGHAR\, PHD CANDIDATE\n_David R. Cheriton School of Com
 puter Science_\n\nWe address the problem of incremental domain adaptation 
 (IDA). We\nassume each domain comes one after another\, and that we could 
 only\naccess data in the current domain. The goal of IDA is to build a\nu
 nified model performing well on all the domains that we have\nencountered.
  We propose to augment a recurrent neural network (RNN)\nwith a directly p
 arameterized memory bank\, which is retrieved by an\nattention mechanism a
 t each step of RNN transition. The memory bank\nprovides a natural way of 
 IDA: when adapting our model to a new\ndomain\, we progressively add new s
 lots to the memory bank\, which\nincreases the number of parameters\, and 
 thus the model capacity. 
DTSTAMP:20260315T060254Z
END:VEVENT
BEGIN:VEVENT
UID:69b64b8e07e7c
DTSTART;TZID=America/Toronto:20181213T160000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20181213T160000
URL:https://uwaterloo.ca/artificial-intelligence-group/events/phd-seminar-b
 eyond-lif-computational-power-passive-dendritic
LOCATION:DC - William G. Davis Computer Research Centre 200 University Aven
 ue West 2310 Waterloo ON N2L 3G1 Canada
SUMMARY:PhD Seminar: Beyond LIF: The Computational Power of Passive Dendrit
 ic\nTrees
CLASS:PUBLIC
DESCRIPTION:ANDREAS STÖCKEL\, PHD CANDIDATE\n_David R. Cheriton School of 
 Computer Science_\n\nThe artificial neurons typically employed in machine 
 learning and\ncomputational neuroscience bear little resemblance to biolog
 ical\nneurons. They are often derived from the “leaky integrate and\nfir
 e” (LIF) model\, neglect spatial extent\, and assume a linear\ncombinati
 on of input variables. It is well known that these\nsimplifications have a
  profound impact on the family of functions that\ncan be computed in a sin
 gle-layer neural network. 
DTSTAMP:20260315T060254Z
END:VEVENT
BEGIN:VEVENT
UID:69b64b8e08d3e
DTSTART;TZID=America/Toronto:20100305T113000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20100305T113000
URL:https://uwaterloo.ca/artificial-intelligence-group/events/ai-seminar-fo
 raging-strategies-artificial-ants
LOCATION:DC - William G. Davis Computer Research Centre 200 University Aven
 ue West 2306C (AI lab) Waterloo ON N2L 3G1 Canada
SUMMARY:AI seminar: Foraging strategies of artificial ants
CLASS:PUBLIC
DESCRIPTION:Speaker: Chris Marriott\, University of Waterloo
DTSTAMP:20260315T060254Z
END:VEVENT
BEGIN:VEVENT
UID:69b64b8e096e1
DTSTART;TZID=America/Toronto:20101112T113000
SEQUENCE:0
TRANSP:TRANSPARENT
DTEND;TZID=America/Toronto:20101112T113000
URL:https://uwaterloo.ca/artificial-intelligence-group/events/ai-seminar-an
 alysis-classification-based-policy-iteration
LOCATION:DC - William G. Davis Computer Research Centre 200 University Aven
 ue West 2306C (AI lab) Waterloo ON N2L 3G1 Canada
SUMMARY:AI seminar: Analysis of classification-based policy iteration\nalgo
 rithms
CLASS:PUBLIC
DESCRIPTION:Speaker: Mohammad Ghavamzadeh\, French Institute for Research i
 n\nComputer Science and Automation (INRIA)\, France
DTSTAMP:20260315T060254Z
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