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DTSTART:20251026T030000
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RDATE:20261025T030000
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UID:calendar.138551.field_date.0@www.tse-fr.eu
DTSTAMP:20260510T171849Z
CREATED:20251029T081002Z
DESCRIPTION:Clément Marteau (Université Lyon I)\, “A non-asymptotic analysi
 s of the single component PLS regression”\, MAD-Stat. Seminar\, Toulouse: 
 TSE\, May 7\, 2026\, 11:00–12:15\, room Auditorium 6.\n\nThis paper invest
 igates some theoretical properties of the Partial Least Square (PLS) metho
 d. We focus our attention on the single component case\, that provides a u
 seful framework to understand the underlying mechanism. We provide a non-a
 symptotic upper bound on the quadratic loss in prediction with high probab
 ility in a high dimensional regression context. The bound is attained than
 ks to a preliminary test on the first PLS component. In a second time\, we
  extend these results to the sparse partial least squares (sPLS) approach.
  In particular\, we exhibit upper bounds similar to those obtained with th
 e lasso algorithm\, up to an additional restricted eigenvalue constraint o
 n the design matrix. (joint with Luca Castelli (PSPM\, ICJ)\, Irène Gannaz
  (G-SCOP\_GROG\, G-SCOP)
DTSTART;TZID=Europe/Paris:20260507T120000
DTEND;TZID=Europe/Paris:20260507T131500
LAST-MODIFIED:20260507T001002Z
LOCATION:Toulouse: TSE\, May 7\, 2026\, 11:00–12:15\, room Auditorium 6
SUMMARY:MAD-Stat. Seminar
URL;TYPE=URI:https://www.tse-fr.eu/seminars/2026-non-asymptotic-analysis-si
 ngle-component-pls-regression
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