We study a variant of the pessimistic bilevel optimization problem, which comprises constraints that must be satisfied for any optimal solution of a subordinate (lower-level) optimization problem. We present conditions that guarantee the existence of optimal solutions in such a problem, and we characterize the computational complexity of various subclasses of the problem. We then focus on probl...

Uplift modeling is a machine learning technique that aims to model treatment effects heterogeneity. It has been used in business and health sectors to predict the effect of a specific action on a given individual. Despite its advantages, uplift models show high sensitivity to noise and disturbance, which leads to unreliable results. In this paper we show different approaches to address the prob...

OBJECTIVE To determine whether optimism predicts lower rates of rehospitalization after coronary artery bypass graft surgery for the 6 months after surgery. METHODS A prospective, inception cohort design was used. The sample consisted of all consenting patients (N=309) from a consecutive series of patients scheduled for elective coronary artery bypass graft surgery at a large, metropolitan ho...

BACKGROUND The authors calculated the effect size for treatments recommended for the pediatric population in the new Guidelines for the Management of Postoperative Nausea and Vomiting that should be implemented with the help of a new risk scale developed for children. METHODS Six single-drug therapies and five combination treatments were subjected to a Bayesian analysis, with respect to the o...

Recently the concept of facility efficiency, which defined by data envelopment analysis (DEA), introduced as a location modeling objective, that provides facilities location’s effect on their performance in serving demands. By combining the DEA models with the location problem, two types of “efficiencies” are optimized: spatial efficiency which measured by finding the least cost location and al...

In this paper, I consider the pessimistic induction construed as a deductive argument (specifically, reductio ad absurdum) and as an inductive argument (specifically, inductive generalization). I argue that both formulations of the pessimistic induction are fallacious. I also consider another possible interpretation of the pessimistic induction, namely, as pointing to counterexamples to the sci...