The goal of causal classification is to identify individuals whose outcome would be positively changed by a treatment. Examples include targeting advertisements and targeting retention incentives to reduce churn. Causal classification is challenging because we observe individuals under only one...

Online platforms often ask their users to refer friends in exchange for a reward. This paper addresses how referral decisions and referral quality evolve throughout the customer's life cycle as a function of service usage, experience level, and past referral behavior. Our analysis is based on a...

Prediction in financial domains is notoriously difficult for a number ofreasons. First, theories tend to be weak or non-existent, which makesproblem formulation open ended by forcing us to consider a large numberof independent variables and thereby increasing the dimensionality ofthe search...

Prior studies have questioned the degree of anonymity of thedouble-blind review process for scholarly research articles. Forexample, one study based on a survey of reviewers concluded that authorsoften could be identified by reviewers using a combination of theauthor's reference list and the...

Model induction from relational data requires aggregation of values ofattributes of related entities. This paper makes three contributions tothe study of relational learning.(1) It presents a hierarchy ofrelational concepts of increasing complexity, using relational schemacharacteristics such as...

Abstract. In many cost-sensitive environments class probabilityestimates are used by decision makers to evaluate the expected utilityfrom a set of alternatives. Supervised learning can be used to buildclass probability estimates; however, it often is very costly to obtaintraining data with class...