In this paper we study the trade-offs between time series compressibility and partial information hiding and their fundamental implications on how we should introduce uncertainty ...
Spiros Papadimitriou, Feifei Li, George Kollios, P...
As a severe threat in anonymized data publication, proximity breach is gaining increasing attention. Such breach occurs when an attacker learns with high confidence that the sensit...
In this paper, we examine the application of manifold learning to the clustering problem. The method used is Locality Preserving Projections (LPP), which is chosen because of its ...
Hassan A. Kingravi, M. Emre Celebi, Pragya P. Raja...
Traditional similarity or distance measurements usually become meaningless when the dimensions of the datasets increase, which has detrimental effects on clustering performance. I...
—Recent advances in mobile handheld devices have facilitated the ubiquitous availability of location based services. Systems which provide location based services have always bee...