Requirements of reactive systems are usually specified by classifying system executions as desirable and undesirable. To specify prioritized requirements, we propose to associate a rank with each execution. This leads to optimization analogs of verification and synthesis problems in which we compute the "best" requirement that can be satisfied or enforced from a given state. The classical defin...

We investigate the problem of using past performance information to select an algorithm for a given classiication problem. We present three ranking methods for that purpose: average ranks, success rate ratios and signiicant wins. We also analyze the problem of evaluating and comparing these methods. The evaluation technique used is based on a leave-one-out procedure. On each iteration, the meth...

UNLABELLED Adolescent suicide is a major social and medical problem. Alcohol use disorders with comorbid major depression represent an especially high-risk profile for suicidal behavior, repeated suicidal behavior and completed suicide. We compared demographic and clinical characteristics, prevalence of interpersonal triggers and the number of triggers for suicidal behavior in depressed late ad...

Given a graph where vertices represent alternatives and arcs represent pairwise comparison data, the statistical ranking problem is to find a potential function, defined on the vertices, such that the gradient of the potential function agrees with the pairwise comparisons. Our goal in this paper is to develop a method for collecting data for which the least squares estimator for the ranking pro...

Solving the person re-identification problem involves matching observations of individuals across disjoint camera views. The problem becomes particularly hard in a busy public scene as the number of possible matches is very high. This is further compounded by significant appearance changes due to varying lighting conditions, viewing angles and body poses across camera views. To address this pro...

Data sparsity, that is a common problem in neighbor-based collaborative filtering domain, usually complicates the process of item recommendation. This problem is more serious in collaborative ranking domain, in which calculating the users’ similarities and recommending items are based on ranking data. Some graph-based approaches have been proposed to address the data sparsity problem, but they ...

Object proposals are an ensemble of bounding boxes with high potential to contain objects. In order to determine a small set of proposals with a high recall, a common scheme is extracting multiple features followed by a ranking algorithm which however, incurs two major challenges: 1) The ranking model often imposes pairwise constraints between each proposal, rendering the problem away from an e...