A selective sampling algorithm is a learning algorithm for classification that, based on the past observed data, decides whether to ask the label of each new instance to be classi...
Many recent techniques for timing analysis under variability, in which delay is an explicit function of underlying parameters, may be described as parameterized timing analysis. T...
In this paper we formalize a general model of cryptanalytic time/memory tradeoffs for the inversion of a random function f : {0, 1, . . . , N - 1} {0, 1, . . . , N - 1}. The model...
We prove a version of the derandomized Direct Product lemma for deterministic space-bounded algorithms. Suppose a Boolean function g : {0, 1}n {0, 1} cannot be computed on more th...
Silhouettes contain rich information about the shape of objects that can be used for recognition and classification. We present a novel approach that allows us to reliably compute...
Lena Gorelick, Meirav Galun, Eitan Sharon, Ronen B...