Biological networks are capable of gradual learning based on observing a large number of exemplars over time as well as of rapidly memorizing specific events as a result of a sin...
Abstract. This work describes schemes for distributing between n servers the evaluation of a function f which is an approximation to a random function, such that only authorized su...
Abstract--This paper presents a framework for privacypreserving Gaussian Mixture Model computations. Specifically, we consider a scenario where a central service wants to learn the...
Abstract. This work addresses a class of total-variation based multilabeling problems over a spatially continuous image domain, where the data fidelity term can be any bounded fun...
Abstract. In order to guarantee that the optimal motif is found, traditional pattern-driven approaches perform an exhaustive search over all candidate motifs of length l. We develo...