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UID:0-1110@lptms.universite-paris-saclay.fr
DTSTART;TZID=Europe/Paris:20260526T110000
DTEND;TZID=Europe/Paris:20260526T120000
DTSTAMP:20260519T074613Z
URL:http://www.lptms.universite-paris-saclay.fr/seminars/lptms-seminar-pie
 rfrancesco-urbani-ipht-gif-sur-yvette/
SUMMARY:LPTMS Seminar: Pierfrancesco Urbani (IPhT\, Gif-sur-Yvette) - Salle
  des séminaires du FAST et du LPTMS\, bâtiment Pascal n°530 - 26 Mai 26
  11:00
DESCRIPTION:Separation of timescales controls feature learning and overfitt
 ing in large neural networks\nPierfrancesco Urbani (IPhT\, Gif-sur-Yvette)
 \n&nbsp\;\n\nUnderstanding how large overparameterized networks can extrac
 t relevant features from meaningful data while simultaneously be so expres
 sive to perfectly interpolate pure noise is a conceptual problem central i
 n machine learning. To address this\, we analyze the out-of-equilibrium\, 
 non-linear\, high-dimensional training dynamics of overparametrized two-la
 yer neural networks using dynamical mean field theory.\n\nOur findings rev
 eal a separation of timescales in training\, leading to several key observ
 ations:\n- A slow timescale linked to the growth in model complexity\;\n- 
 An inductive bias towards low complexity when the initial model complexity
  is sufficiently small\;\n- A dynamical decoupling between feature learnin
 g and overfitting phases\;\n- A non-monotonic trend in test error\, charac
 terized by a "feature unlearning" regime at later stages of training.\n\nJ
 oint work with Andrea Montanari.
CATEGORIES:seminars
LOCATION:Salle des séminaires du FAST et du LPTMS\, bâtiment Pascal n°53
 0\, rue André Riviere\, Orsay\, 91405\, France
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=rue André Riviere\, Orsay\
 , 91405\, France;X-APPLE-RADIUS=100;X-TITLE=Salle des séminaires du FAST 
 et du LPTMS\, bâtiment Pascal n°530:geo:0,0
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DTSTART:20260329T030000
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