This paper adresses the variance quantification problem for system identification based on the prediction error framework. The role of input and model class selection for the auto-...
We analyze the complexity of propositional kernel resolution (del Val 1999), a general method for obtaining logical consequences in restricted target languages. Different choices ...
In this paper, we propose a Gaussian Process Regression (GPR) framework for concealment of corrupted motion vectors in predictive video coding of packet video systems. The problem...
Hadi Asheri, Abdolkhalegh Bayati, Hamid R. Rabiee,...
Kernel functions have become an extremely popular tool in machine learning, with an attractive theory as well. This theory views a kernel as implicitly mapping data points into a ...
In this paper a novel non-linear subspace method for face verification is proposed. The problem of face verification is considered as a two-class problem (genuine versus imposto...