We propose the combination of two recently introduced methods for the interactive visual data mining of large collections of data. Both, Hyperbolic Multi-Dimensional Scaling (HMDS...
Random projection (RP) is a common technique for dimensionality reduction under L2 norm for which many significant space embedding results have been demonstrated. However, many si...
During the last years, the growing application complexity, design, and mask costs have compelled embedded system designers to increasingly consider partially reconfigurable applica...
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...
In this paper, we present a pseudo-collision attack on the compression function of all Twister variants (224,256,384,512) with complexity of about 226.5 compression function evalua...
Florian Mendel, Christian Rechberger, Martin Schl&...