UofH_City_Campus_Nitzan_Zohar_01-2020-08

Prof. DAN FELDMAN

Prof. Feldman is a worldwide leader and main developer both in 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, (current\modern) applications include Machine/Deep learning of Big Data, Robotics, Computer Vision, Cybersecurity, and many more. 

RECENT PUBLICATIONS

k-Means+++: Outliers-Resistant Clustering
A Statman, L Rozenberg, D Feldman
Sphere Fitting with Applications to Machine Tracking
D Epstein, D Feldman; Algorithms 13 (8), 177
Aligning Points to Lines: Provable Approximations
I Jubran, D Feldman; IEEE Transactions on Knowledge and Data Engineering