Secure Federated Matrix Factorization

Tensor Factorization via Matrix Factorization

Tensor factorization arises in many machinelearning applications, such knowledge basemodeling and parameter estimation in latentvariable models. However, numerical meth-ods for tensor factorization have not reachedthe level of maturity of matrix factorizationmethods. In this paper, we propose a newmethod for CP tensor factorization that usesrandom projections to ...

Matrix Factorization and Matrix Concentration

Matrix Factorization and Matrix Concentration by Lester Wayne Mackey II Doctor of Philosophy in Electrical Engineering and Computer Sciences with the Designated Emphasis in Communication, Computation, and Statistics University of California, Berkeley Professor Michael I. Jordan, Chair Motivated by the constrained factorization problems of sparse principal components analysis (PCA) for gene expr...

Secure Federated Data Retrieval in Clinical Trials

The clinical domain is one in which a plethora of data exists in repositories distributed across the globe, crossing institutional, regional and national boundaries. To be able to harness this data and move it across these boundaries has the potential to provide great scientific and medical insight, to the benefit of many protagonists in the field of clinical medicine. In this paper, we outline...

Towards a Secure Federated Information System

Secure Mobile Nodes in Federated Databases

Mobile computers pose special security risks since information contained on them can more easily be compromised. However, availability of information at the location where the mobile computer is to be used often outweighs the disadvantages. This paper proposes an approach to limit the risks of information compromise by caching only that information on the mobile computer that the user of the mo...