Software used in embedded systems is subject to strict timing and space constraints. The growing software complexity creates an urgent need for fast program execution under the co...
In this paper, we present an efficient model for discovering repeated patterns in symbolic representations of music. Combinatorial redundancy inherent to the pattern discovery pa...
Subspace learning techniques are widespread in pattern recognition research. They include Principal Component Analysis (PCA), Locality Preserving Projection (LPP), etc. These tech...
We present a probabilistic model for a document corpus that combines many of the desirable features of previous models. The model is called “GaP” for Gamma-Poisson, the distri...
Learning curves for Gaussian process (GP) regression can be strongly affected by a mismatch between the ‘student’ model and the ‘teacher’ (true data generation process), e...