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SUMMARY:Deep-layered machines have a built-in Occam's razor - Thomas Fink 
 (Director\, The London Institute for Mathematical Sciences)
DTSTART:20260311T120000Z
DTEND:20260311T130000Z
UID:TALK245638@talks.cam.ac.uk
CONTACT:Mateja Jamnik
DESCRIPTION:Input-output maps are prevalent throughout science and technol
 ogy. They are empirically observed to be biased towards simple outputs\, b
 ut we don’t understand why. To address this puzzle\, we study the archet
 ypal input-output map: a deep-layered machine in which every node is a Boo
 lean function of all the nodes below it. We give an exact theory for the d
 istribution of outputs\, and we confirm our predictions through extensive 
 computer experiments. As the network depth increases\, the distribution be
 comes exponentially biased towards simple outputs. This suggests that deep
 -layered machines and other learning methodologies may be inherently biase
 d towards simplicity in the models that they generate.\n\n"Zoom link for o
 nline participants":https://cl-cam-ac-uk.zoom.us/j/6590822098\, Meeting ID
 : 659 082 2098 Passcode: 1dYRka\n\n
LOCATION:Computer Laboratory\, William Gates Building\, Room FW26
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