Abstract: Privacy-preserving data analysis has been put on a firm mathematical foundation since the introduction of differential privacy (DP) in 2006. This privacy definition, however, has some well-known weaknesses: notably, it does not tightly handle composition. This weakness has inspired several recent relaxations of differential privacy based on the Renyi divergences. We propose an alternative…
Interested in starting your data science journey? Register for this special free virtual event. You'll receive a confirmation e-mail with further details about the webinar. Demand for professionals skilled in data, analytics, and machine learning is exploding. A recent report by IBM and Burning Glass states that there will be 364K new job openings in…
Abstract:Â We introduce the diffusion K-means clustering method on Riemannian submanifolds, which maximizes the within-cluster connectedness based on the diffusion distance. The diffusion K-means constructs a random walk on the similarity graph with vertices as data points randomly sampled on the manifolds and edges as similarities given by a kernel that captures the local geometry of…
TBD
TBD
About the speaker: Rohini Pande is the Henry J. Heinz II Professor of Economics and Director of the Economic Growth Center, Yale University. She is a co-editor of American Economic Review: Insights. Pande’s research is largely focused on how formal and informal institutions shape power relationships and patterns of economic and political advantage in society,…
This one-day technical conference brings together local academic leaders, industrial professionals and students to hear about the latest data science-related research in a number of domains, to learn how leading-edge companies are leveraging data science for success, and to connect with potential mentors, collaborators, and others in the field.
TBD
TBD
TBD