We study sparse principal components analysis in the high-dimensional setting, where p (the number of variables) can be much larger than n (the number of observations). We prove o...
Starting with a similarity function between objects, it is possible to define a distance metric (the kernel distance) on pairs of objects, and more generally on probability distr...
Sarang C. Joshi, Raj Varma Kommaraju, Jeff M. Phil...
The trend to multi-core chip designs presents new challenges for design automation, while the increased reuse of components may offer solutions. This paper describes some of the k...
We propose a new algorithm for independent component and independent subspace analysis problems. This algorithm uses a contrast based on the Schweizer-Wolff measure of pairwise de...
Interaction analysis within online educational contexts based on collaborative learning strategies requires a multidimensional model taking into account social, emotional and cogni...