We study single-item single-unit Bayesian posted price auctions, where buyers arrive
sequentially and their valuations for the item being sold depend on a random, unknown …

Online data marketplaces emerge in diverse data-driven applications, where dynamically
arriving consumers pur-chase the data at posted prices. The data value decays over time in …

Abstract Machine Learning algorithms are increasingly being deployed in consequential
decision-making for people's lives. These decisions affect widely different aspects of our …

In this work, we investigate online mechanisms for trading time-sensitive valued data. We
adopt a continuous function $ d (t) $ to represent the data value fluctuation over time $ t …

With the rapid growth of the applications in AI, the demand of data has increased
significantly. To facilitate the circulation of data, numerous online data sharing and trading …

We study contextual search, a generalization of binary search in higher dimensions, which
captures settings such as feature-based dynamic pricing. Standard formulations of this …

This thesis revolves around the problem of selling and advertising products on the Web and
exploits techniques from the fields of algorithmic game theory, mechanism design, and …

The elasticity of the demand with respect to the price of a good have always been a key
indicator in the field of pricing. In the process of deciding the correct price for a product, its …

Most of the economic reports forecast that artificial intelligence (AI) will unlock up to 12
trillion USD per year worldwide by the next decade, and almost half of this amount will …

The elasticity of the demand with respect to the price of a good have always been a key
indicator in the field of pricing. In the process of deciding the correct price for a product, its …