Lossless condensers are unbalanced expander graphs, with expansion close to optimal. Equivalently, they may be viewed as functions that use a short random seed to map a source on ...
We give new constructions of randomness extractors and lossless condensers that are optimal to within constant factors in both the seed length and the output length. For extractor...
Venkatesan Guruswami, Christopher Umans, Salil P. ...
In recent years, privacy preserving data mining has become an important problem because of the large amount of personal data which is tracked by many business applications. In many...
Abstract. In this paper, some new approaches to training set size reduction are presented. These schemes basically consist of defining a small number of prototypes that represent ...
In this paper, we propose a new data reduction algorithm that iteratively selects some samples and ignores others that can be absorbed, or represented, by those selected. This alg...