Therehasbeensurprisinglylittle researchso far that systematicallyinvestigatedthe possibilityof constructinghybrid learningalgorithmsbysimplelocal modificationsto decision tree lea...
Alexander K. Seewald, Johann Petrak, Gerhard Widme...
In a data word or a data tree each position carries a label from a finite alphabet and a data value from some infinite domain. These models have been considered in the realm of sem...
Skyline queries have gained a lot of attention for multicriteria analysis in large-scale datasets. While existing skyline algorithms have focused mostly on exploiting data dominan...
Phylospaces is a novel framework for reconstructing evolutionary trees in tuple space, a distributed shared memory that permits processes to communicate and coordinate with each o...
Kernel methods are effective approaches to the modeling of structured objects in learning algorithms. Their major drawback is the typically high computational complexity of kernel ...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...