Earth observation data underpin climate science, disaster response, and environmental policy, yet inconsistent grid definitions often limit their accuracy and reuse. Researchers now present a unified, ...

Intrinsic dimensionality estimation seeks to determine the minimum number of variables required to describe the structure underlying high-dimensional datasets. By identifying the true manifold that ...

Joanna Riley, CEO & cofounder of Censia. Striving for a more just and efficient global economy through better talent data and technology. In the age of data-driven decision-making, the significance of ...

The popularity of Microsoft Excel has never waned. Today, a whopping 1.1 billion users globally rely on it for multidimensional analysis in areas such as "scenario planning, supply chain optimization, ...

This book offers a comprehensive framework for mastering the complexities of learning high-dimensional sparse graphical models through the use of conditional independence tests. These tests are ...

Welcome to Multidimensional Data Reversion, a four-part podcast series from Ropes & Gray’s Insights Lab where data analysis intersects with the law. On this first episode, join Shannon Capone Kirk, ...

It is a significant and challenging task to detect the informative features to carry out explainable analysis and build an interpretable AI system for high dimensional data, especially for those with ...

Your source for the news, opinions, and reader reaction on the industry’s hottest controversy. Excerpt from Microsoft SQL Server 2008 Analysis Services Unleashed. Working with relational databases, we ...

On this bonus episode of Ropes & Gray’s Insights Lab’s Multidimensional Data Reversion podcast series, Shannon Capone Kirk and David Yanofsky are joined by Michelle DiMartino, a cultural psychologist, ...

Dorothy Foehr Huck and J. Lloyd Huck Chair in Neuroethics, Associate Professor of Engineering Science and Mechanics, Associate Professor of Philosophy and Bioethics, Associate Director Neuroethics and ...