In this paper we prove a theorem that gives an (almost) tight upper bound on the sensitivity of a multiple-output Boolean function in terms of the sensitivity of its coordinates an...
This paper presents a new approach for designing test sequences to be generated on–chip. The proposed technique is based on machine learning, and provides a way to generate effi...
Christophe Fagot, Patrick Girard, Christian Landra...
In this paper we prove a perhaps unexpected relationship between the complexity class of the boolean functions that have linear size circuits, and n-party private protocols. Speci...
Eyal Kushilevitz, Rafail Ostrovsky, Adi Rosé...
We quantatively analyze the differences between a realistic mobility model, TRANSIMS, and several synthetic mobility models. New synthetic models were created by modifying the sta...
D. Charles Engelhart, Anand Sivasubramaniam, Chris...
If the dataset available to machine learning results from cluster sampling (e.g. patients from a sample of hospital wards), the usual cross-validation error rate estimate can lead...