This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
Abstract. So far, most methods for identifying sequences under selection based on comparative sequence data have either assumed selectional pressures are the same across all branch...
Adam C. Siepel, Katherine S. Pollard, David Haussl...
We present a novel structure-enhancing adaptive filter guided by features derived from the Gradient Structure Tensor. We employ this filter to reduce noise in seismic data and to ...
Choosing an appropriate kernel is one of the key problems in kernel-based methods. Most existing kernel selection methods require that the class labels of the training examples ar...
In this paper, we propose a technique for segmenting visual textures using features extracted from the reponses of Ga,bor filters, appropria.tely selectecl to be tuned to texture ...