This paper performs a comprehensive investigation of dynamic selection for long atomic traces. It introduces a classification of trace selection methods and discusses existing and...
Abstract. Data declustering speeds up large data set retrieval by partitioning the data across multiple disks or sites and performing retrievals in parallel. Performance is determi...
Hak-Cheol Kim, Mario A. Lopez, Scott T. Leutenegge...
Many real-world data mining tasks require the achievement of two distinct goals when applied to unseen data: first, to induce an accurate preference ranking, and second to give g...
This paper studies the ensemble selection problem for unsupervised learning. Given a large library of different clustering solutions, our goal is to select a subset of solutions t...
In this paper a method suitable for partial matching between 3D objects is presented. The 3D objects are firstly segmented into meaningful parts extending a method which is based ...