Graphical Models for Economic Profit Maximization

MAP Estimation for Graphical Models by Likelihood Maximization

Computing a maximum a posteriori (MAP) assignment in graphical models is a crucial inference problem for many practical applications. Several provably convergent approaches have been successfully developed using linear programming (LP) relaxation of the MAP problem. We present an alternative approach, which transforms the MAP problem into that of inference in a mixture of simple Bayes nets. We ...

Optimal Ad-Ranking for Profit Maximization

Despite the enormous commercial importance of on-line advertisements (ads), there has been little work done to clarify the basis for ranking and displaying them. Most existing methods rank ads as if the user views each of them in isolation. We will consider a more realistic user model that induces three mutual influences between displayed ads: (i) positional bias (for viewing ads placed higher ...

Customer Selection and Profit Maximization

Profit Maximization and Supermodular Technology

A dataset is a list of observed factor inputs and prices for a technology; profits and production levels are unobserved. We obtain necessary and sufficient conditions for a dataset to be consistent with profit maximization under a monotone and concave revenue based on the notion of cyclic monotonicity. Our result implies that monotonicity and concavity cannot be tested, and that one cannot deci...

Profit Maximization in Cloud Computing

Cloud computing is a novel paradigm for the provision of computing infrastructure, which aims to shift the location of the computing infrastructure to the network in order to reduce the costs of management and maintenance of hardware and software resources. To maximize the profit, a service provider should understand both service charges and business costs. Our pricing model takes such factors ...