Prof. DAN FELDMAN

Prof. Feldman is a worldwide leader and main developer both in the academy and industry for the research field known as core sets: a provably small and problem dependent data reduction.  While the theory is based on deep computational geometry, applications these days include Machine/Deep learning of Big Data, Robotics, Computer Vision, Cybersecurity, and many more. 

SELECTED PROJECTS

RECENT PROJECTS

RECENT PUBLICATIONS

Turning Big Data Into Tiny Data: Constant-Size Coresets for -Means, PCA, and Projective Clustering
Dan Feldman, Melanie Schmidt, Christian Sohler; SIAM Journal on Computing 49 (3), 601-657
Real-time EEG classification via coresets for BCI applications
E Netzer, A Frid, D Feldman; Engineering Applications of Artificial Intelligence 89, 103455
Secure k-ish nearest neighbors classifier
H Shaul, D Feldman, D Rus; Proceedings on Privacy Enhancing Technologies 2020 (3), 42-61