Abstract. We propose a novel method for addressing the model selection problem in the context of kernel methods. In contrast to existing methods which rely on hold-out testing or t...
Motion information scalability is an important requirement for a fully scalable video codec, especially in low bit rate or small resolution decoding scenarios, for which the fully...
Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially ...
Antti Honkela, Matti Tornio, Tapani Raiko, Juha Ka...
This paper presents a novel system that employs an adaptive neural network for the no-reference assessment of perceived quality of JPEG/JPEG2000 coded images. The adaptive neural ...
We present a practical, stratified autocalibration algorithm with theoretical guarantees of global optimality. Given a projective reconstruction, the first stage of the algorithm ...