The wide variety of pricing policies used in practice by data-sellers suggests that there are significant challenges in pricing datasets. In this paper, we develop a utility framework that is appropriate for data-buyers and the corresponding pricing of the data by the data-seller. A buyer...

In many practical settings, learning algorithms can take a substantial amount of time to converge, thereby raising the need to understand the role of discounting in learning. We illustrate the impact of discounting on the performance of learning algorithms by examining two classic and...

We study a multiproduct pricing problem in which the prices of the products are restricted to discrete and finite sets. The demand for a product is a function of the prices of all the products. The prices of the products can be changed through time, subject to the aggregate consumption of each...