Abstract. In property testing, the goal is to distinguish between structures that have some desired property and those that are far from having the property, after examining only a...
This paper deals with an unusual phenomenon where most machine learning algorithms yield good performance on the training set but systematically worse than random performance on th...
—The concept of differential privacy as a rigorous definition of privacy has emerged from the cryptographic community. However, further careful evaluation is needed before we ca...
Keeping diagnostic resolution as high as possible while maximizing the compaction ratio is subject to research since the advent of embedded test. In this paper, we present a novel...
Abstract. We establish a generic theoretical tool to construct probabilistic bounds for algorithms where the output is a subset of objects from an initial pool of candidates (or mo...