This paper proposes a method of finding a discriminative linear transformation that enhances the data's degree of conformance to the compactness hypothesis and its inverse. Th...
We study similarity queries for time series data where similarity is defined in terms of a set of linear transformations on the Fourier series representation of a sequence. We hav...
We study similarity queries for time series data where similarity is defined in terms of a set of linear transformations on the Fourier series representation of a sequence. We ha...
To obtain classification systems with both good generalizat`ion performance and efficiency in space and time, we propose a learning method based on combinations of weak classifiers...
In this paper, we propose a linear model-based general framework to combine k-best parse outputs from multiple parsers. The proposed framework leverages on the strengths of previo...