We study the learnability of sets in Rn under the Gaussian distribution, taking Gaussian surface area as the “complexity measure” of the sets being learned. Let CS denote the ...
Adam R. Klivans, Ryan O'Donnell, Rocco A. Servedio
Statistical learning theory chiefly studies restricted hypothesis classes, particularly those with finite Vapnik-Chervonenkis (VC) dimension. The fundamental quantity of interest i...
In this paper we give a robust logical and computational characterisation of peer-to-peer (p2p) database systems. We first define a precise model-theoretic semantics of a p2p sys...
Enrico Franconi, Gabriel M. Kuper, Andrei Lopatenk...
Most protocols for distributed, fault-tolerant computation, or multi-party computation (MPC), provide security guarantees in an all-or-nothing fashion: If the number of corrupted p...
In this paper, we study the wireless synchronization problem which requires devices activated at different times on a congested single-hop radio network to synchronize their roun...