Machine Learning and Regularization

ESEM
Presenter(s) Type Length Chair
Andrii Babii Jungjun Choi Yukun Ma Mario Martinoli Contributed 25/08 09:00 UTC
90
mins
Anders Kock

Papers

(Listed in order of presenters above)

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

Read paper

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

Read paper

Nonparametric Moment-based Estimation of Simulated Models via Regularized Regression

Read paper