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UID:8722@i2m.univ-amu.fr
DTSTART;TZID=Europe/Paris:20250922T140000
DTEND;TZID=Europe/Paris:20250922T160000
DTSTAMP:20250916T075846Z
URL:https://www.i2m.univ-amu.fr/evenements/luc-brogat-motte/
SUMMARY:Luc Brogat-Motte (Istituto Italiano di Tecnologia): Provably Effici
 ent Supervised Learning Algorithms for Non-i.i.d. and Structured Data
DESCRIPTION:Luc Brogat-Motte: \n\nThis talk will present recent contributio
 ns and ongoing directions in supervised learning for non-i.i.d. and struct
 ured data. It will present algorithms that are both efficient in practice 
 and come with formal performance guarantees. These approaches are availabl
 e as open-source software and have been validated on both synthetic benchm
 arks and real-world datasets.\n\nThe first part will focus on structured p
 rediction methods designed to overcome the curse of the output dimension\,
  providing finite-sample learning bounds and computational complexity guar
 antees\, and demonstrating significant empirical improvements over state-o
 f-the-art approaches in applications such as metabolite identification.\n\
 nThe second part will address learning from time-dependent data\, combinin
 g statistical learning theory with stochastic calculus to develop estimati
 on methods for continuous-time\, nonlinear stochastic dynamical systems. P
 articular attention will be given to stochastic differential equation esti
 mation and to safe learning for controlled systems under uncertainty\, wit
 h applications in areas such as robotics and biology.\n
CATEGORIES:Séminaire,Statistique
LOCATION:Saint-Charles - FRUMAM  (2ème étage)\, 3 Place Victor Hugo\, Mar
 seille\, 13003\, France
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=3 Place Victor Hugo\, Marse
 ille\, 13003\, France;X-APPLE-RADIUS=100;X-TITLE=Saint-Charles - FRUMAM  (
 2ème étage):geo:0,0
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DTSTART:20250330T030000
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