Abstract. Subspace mapping methods aim at projecting high-dimensional data into a subspace where a specific objective function is optimized. Such dimension reduction allows the re...
Axel J. Soto, Marc Strickert, Gustavo E. Vazquez, ...
In this work we present the Partner Units Problem as a novel challenge for optimization methods. It captures a certain type of configuration problem that frequently occurs in indu...
Markus Aschinger, Conrad Drescher, Gerhard Friedri...
Many factorization models like matrix or tensor factorization have been proposed for the important application of recommender systems. The success of such factorization models dep...
While extensive work has been done on evaluating queries over tuple-independent probabilistic databases, query evaluation over correlated data has received much less attention eve...
— Differential privacy has recently emerged as the de facto standard for private data release. This makes it possible to provide strong theoretical guarantees on the privacy and ...
Graham Cormode, Cecilia M. Procopiuc, Divesh Sriva...