[Statlist] Reminder: ETH/UZH Research Seminar by Mona Azadkia, ETH Zürich, 21.10.2022

[Kaiser-Heinzmann Susanne]

We are glad to announce the following talk in the ETH/UZH Research Seminar:

"Linear regression with unmatched data: a deconvolution perspective"   
by Mona Azadkia, ETH Zürich

Time: Friday,  21.10.22 at 15.15 h
Place: ETH Zurich, HG G 19.1

Abstract: Consider the regression problem where the response Y∈ ℝ and the covariate X ∈ ℝ^d for d≥1 are unmatched. Under this scenario, we do not have access to pairs of observations from the distribution of (X,Y), but instead, we have separate datasets {Yi}_ni=1 and {Xj}_mj=1, possibly collected from different sources. We study this problem assuming that the regression function is linear and the noise distribution is known or can be estimated. We introduce an estimator of the regression vector based on deconvolution and demonstrate its consistency and asymptotic normality under an identifiability assumption. In the general case, we show that our estimator (DLSE: Deconvolution Least Squared Estimator) is consistent in terms of an extended ℓ2 norm. Using this observation, we devise a method for semi-supervised learning, i.e., when we have access to a small sample of matched pairs (Xk,Yk). Several applications with synthetic and real datasets are considered to illustrate the theory.


Seminar website: https://math.ethz.ch/sfs/news-and-events/research-seminar.html

Research Seminar – Seminar for Statistics | ETH Zurich
math.ethz.ch


Organisers: A. Bandeira, P. L. Bühlmann, R. Furrer, L. Held, T. Hothorn, D. Kozbur, M. H. Maathuis, N. Meinshausen, S. van de Geer, M. Wolf