Background: Several supervised and unsupervised learning tools are available to classify functional genomics data. However, relatively less attention has been given to exploratory...
We study the distributed sampling and centralized reconstruction of two correlated signals, modeled as the input and output of an unknown sparse filtering operation. This is akin ...
Ali Hormati, Olivier Roy, Yue M. Lu, Martin Vetter...
Heterogeneous wireless/wired networks and ubiquitous environments are gaining ever more attention by research community. To properly control and manage such puzzles a deep knowled...
This paper presents a data-driven approach for segmenting range data to enable a humanoid robot to perform interactive domestic tasks. Range data is segmented into geometric primi...
We present a class of algorithms for independent component analysis (ICA) which use contrast functions based on canonical correlations in a reproducing kernel Hilbert space. On th...