The k-anonymization method is a commonly used privacy-preserving technique. Previous studies used various measures of utility that aim at enhancing the correlation between the orig...
The design of a good kernel is fundamental for knowledge discovery from graph-structured data. Existing graph kernels exploit only limited information about the graph structures bu...
— Recent work [12] shows that conventional privacy preserving publishing techniques based on anonymity-groups are susceptible to corruption attacks. In a corruption attack, if th...
—We describe parallel methods for solving large-scale, high-dimensional, sparse least-squares problems that arise in machine learning applications such as document classificatio...
—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...