The Web has been one of the most impactful technologies ever, and over the past twenty years or so, has helped advance society in ways no one thought possible. Ubiquitous connectivity has enabled instant communication with anyone in the world. Social media has helped us strengthen existing relationships, and form new ones. The vast amount of content on the Web has broadened our outlook, and let us learn about things we never even knew existed.
Pairwise learning refers to a learning task which involves a loss function depending on pairs of examples, among which most notable ones include bipartite ranking, metric learning, minimum entropy error and AUC maximization. Online learning algorithms consider one instance each time to update the model sequentially, which make them amenable for streaming data analysis. However, most of such algorithms focused on the pointwise learning problems such as classification and regression.
The mission of the RARE Center is to advance the field of astrobiology by catalyzing innovative and interdisciplinary research through novel training and educational programs, and by modeling serving as a platform to evolve a multidisciplinary collection of research programs into a truly interdisciplinary and interactive collaborative network. The RARE Center brings together researchers from across RPI, along with national and international colleagues and partners, who are broadly interested in the field of Astrobiology.
The Tetherless World Constellation (TWC) at Rensselaer Polytechnic Institute (RPI) is a constellation of multidisciplinary researchers who study the scientific and engineering principles that underlie the Web, to enhance the Web's reach beyond the desktop and laptop computer, and develops new technologies and languages that expand the capabilities of the Web under three themes: Future Web, Xinformatics and Semantic Foundations.
Complex problems require interdisciplinary solutions. The Rensselaer Data Science Research Center develops the technologies to enable that multidisciplinary research. The center acquires, processes, archives, analyzes, model, visualizes, simulates, and disseminates complex data to close the data-to-knowledge gap across multiple time and length scales.
The Jefferson Project at Lake George—a collaboration between Rensselaer Polytechnic Institute, IBM Research, and The FUND for Lake George—is an unprecedented technological approach to studying fresh water so we can understand impacts of human activities and how to mitigate those effects. The Jefferson Project combines Internet-of-Things technology and powerful analytics with lake and atmospheric science to create a new model for environmental monitoring and prediction.
A health-care data expert (IDEA Associate Director Kristin Bennett) and a biomedical engineer discuss how data analysis can be used to tackle today’s biggest health challenges.
In 2012, seeing the emergence of a link between big data, Artificial Intelligence, and data science, I was asked by President Jackson if I would h