Abstract. Kernel based methods (such as k-nearest neighbors classifiers) for AI tasks translate the classification problem into a proximity search problem, in a space that is usu...
High dimensional data has always been a challenge for clustering algorithms because of the inherent sparsity of the points. Recent research results indicate that in high dimension...
A powerful combinational path sensitization engine is required for the efficient implementation of tools for test pattern generation, timing analysis, and delay fault testing. Path...
Tsochantaridis et al. (2005) proposed two formulations for maximum margin training of structured spaces: margin scaling and slack scaling. While margin scaling has been extensivel...
We followed the work of an international research network that holds regular meetings in technology-enhanced environments. The team is geographically distributed and to support its...