In this paper we give approximation algorithms for several proximity problems in high dimensional spaces. In particular, we give the rst Las Vegas data structure for (1 + )-neares...
We consider probabilistic inference in general hybrid networks, which include continuous and discrete variables in an arbitrary topology. We reexamine the question of variable dis...
Data captured from a live cellular network with the real users during their common daily routine help to understand how the users move within the network. Unlike the simulations wi...
New emerging scientific applications in geosciences, sensor and spatio-temporal domains require adaptive analysis frameworks that can handle large datasets with multiple dimension...
We present a theoretical analysis of supervised ranking, providing necessary and sufficient conditions for the asymptotic consistency of algorithms based on minimizing a surrogate...