Current on-chip block-centric memory hierarchies exploit access patterns at the fine-grain scale of small blocks. Several recently proposed techniques for coherence traffic reduct...
We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...
Time is an important data dimension with distinct characteristics that is common across many application domains. This demands specialized methods in order to support proper analy...
Wolfgang Aigner, Alessio Bertone, Silvia Miksch, C...
The creation of a complex web site is a thorny problem in user interface design. In this paper we explore the notion of adaptive web sites: sites that semi-automatically improve t...
In this paper, we address the issue of transducing the object cutout model from an example image to novel image instances. We observe that although object and background are very ...