We propose new and improved instantiations of lossy trapdoor functions (Peikert and Waters, STOC ’08), and correlation-secure trapdoor functions (Rosen and Segev, TCC ’09). Ou...
David Mandell Freeman, Oded Goldreich, Eike Kiltz,...
We present a novel linear clustering framework (DIFFRAC) which relies on a linear discriminative cost function and a convex relaxation of a combinatorial optimization problem. The...
This paper concerns the design of a Support Vector Machine (SVM) appropriate for the learning of Boolean functions. This is motivated by the need of a more sophisticated algorithm ...
An (n, m, k)-resilient function is a function f : Fn 2 → Fm 2 such that every possible output m-tuple is equally likely to occur when the values of k arbitrary inputs are fixed ...
Background: Information obtained from diverse data sources can be combined in a principled manner using various machine learning methods to increase the reliability and range of k...
Bolan Linghu, Evan S. Snitkin, Dustin T. Holloway,...