Problem definition: The recent advent of data-driven and end-to-end decision-making across
different areas of operations management has led to an ever closer integration of prediction …

Adversarially robust optimization (ARO) has become the de facto standard for training models
to defend against adversarial attacks during testing. However, despite their robustness, …

Maximizing a convex function over convex constraints is an NP-hard problem in general.
We prove that such a problem can be reformulated as an adjustable robust optimization (ARO) …

In recent years, differential privacy has emerged as the de facto standard for sharing statistics
of datasets while limiting the disclosure of private information about the involved individuals…

Recent work has leveraged the popular distributionally robust optimization paradigm to
combat overfitting in classical logistic regression. While the resulting classification scheme …

We study non-convex optimization problems over simplices. We show that for a large class
of objective functions, the convex approximation obtained from the Reformulation-…

We introduce a solution scheme for portfolio optimization problems with cardinality constraints.
Typical portfolio optimization problems are extensions of the classical Markowitz mean–…

When the inputs of a machine learning model are subject to adversarial attacks, standard
stationarity assumptions on the training and test sets are violated, typically making empirical …

… Erkekler ve kadınların yaş ortalamaları arası farklılıklar istatistiksel olarak anlamlı
bulunmadı … Ölçülen parametreler arası korelasyon Tablo 4.10.’da yer almaktadır. Ölçülen …

Background Vitamin D deficiency is known to cause increased predisposition to various
infectious diseases and the addition of vitamin D to antimicrobial treatment may improve …