Machine Learning and Regularization

ESEM
Presenter(s) Type Archive date Archive time Length
Andrii Babii
Jungjun Choi
Yukun Ma
Mario Martinoli
Contributed
25/08/21
11:00 CEST
90 mins
Presenter(s)
Type
Archive date
25/08/21
Archive time
11:00 CEST
Length
90 mins

Papers

(Listed in order of presenters above)

Binary choice with asymmetric loss in a data-rich environment: theory and an application to racial justice

Inference using Nuclear-norm Penalized Estimator and Its Applications

Dyadic Machine Learning: with an Application to High-Dimensional Dyadic-Robust Analysis of Determinants of Free Trade Agreements

Nonparametric Moment-based Estimation of Simulated Models via Regularized Regression