Researchers have shown that deep learning models are susceptible to adversarial
examples, however, most existing works focus on supervised learning. Recently, research …

Online marketplaces must optimize recommendations with regards to multiple objectives, in
order to fulfill expectations from a variety of stakeholders. This problem is typically …

Machine Learning (ML) models are being deployed in numerous applications, ranging from
autonomous vehicles to robotics. However, the performance of these ML models is highly …

This paper addresses and evaluates approaches to incorporating personality data into a
recommender system. Automatic personality recognition is enabled by the LIWC dictionary …

With the rapid development of artificial intelligence, the selection of algorithms that meet
application requirements from feasible algorithms has become a critical problem to be …

We propose a methodology, based on machine learning and optimization, for selecting a
solver configuration for a given instance. First, we employ a set of solved instances and …

Automatic configuration of algorithmic parameters is an area of active research [16, 27],
going back to the foundational work [33], published in 1976. The algorithm configuration …

The research topics described in this Ph. D. thesis lie at the intersection of Machine Learning
(ML) and Mathematical Programming (MP). The main contributions concern the Algorithm …