The goal of this workshop is to study the challenges in learning, evaluating, and mining of data from e-commerce and more classical commerce domains. As the largest commerce and e-commerce companies on the planet are adopting machine learning technologies, whether to make available an ever-growing number of products, to power new differentiated experiences, or to better understand their customers, it becomes increasingly clear that these domains present different challenges that classical machine learning problems. 

We will consider, among others, problems such as identifying dysfunctional items or collections in a website, off-policy evaluation of marketing strategies, personalization of e-commerce experience, validation, sequential decisions, dynamic pricing, and others. Also, we will focus on the problems themselves more than on solutions. 

Invited Speakers

Organizers