Data marketplaces are expected to play a crucial role in tomorrow's data economy, but such
marketplaces are seldom commercially viable. Currently, there is no clear understanding of …

Abstract Machine learning is disruptive. At the same time, machine learning can only
succeed by collaboration among many parties in multiple steps naturally as pipelines in an …

Federated learning (FL) is a popular technique to train machine learning (ML) models on
decentralized data sources. In order to sustain long-term participation of data owners, it is …

Given a data set $\mathcal {D} $ containing millions of data points and a data consumer who
is willing to pay for\$$ X $ to train a machine learning (ML) model over $\mathcal {D} $, how …

Big data is considered to be the key to unlocking the next great waves of growth in
productivity. The amount of collected data in our world has been exploding due to a number …

Data are invaluable. How can we assess the value of data objectively, systematically and
quantitatively? Pricing data, or information goods in general, has been studied and practiced …

Data only generates value for a few organizations with expertise and resources to make
data shareable, discoverable, and easy to integrate. Sharing data that is easy to discover …

Big data has been advocated as a dominant driving force to unleash the great waves of the
next-generation industrial revolution. While the ever-increasing proliferation of …

Federated learning is an emerging decentralized machine learning scheme that allows
multiple data owners to work collaboratively while ensuring data privacy. The success of …

Data analytics using machine learning (ML) has become ubiquitous in science, business
intelligence, journalism and many other domains. While a lot of work focuses on reducing …