Sub-dominant theory provides efficient tools for clustering. However it classically works only for ultrametrics and ad hoc extensions like Jardine and Sibson's 2ultrametrics....
- Contiguity Analysis is a straightforward generalization of Linear Discriminant Analysis in which the partition of elements is replaced by a more general graph structure. Applied ...
The problem of clustering is often addressed with techniques based on a Voronoi partition of the data space. Vector quantization is based on a similar principle, but it is a diffe...
This paper presents a new approach to speech synthesis in which a set of cross-word decision-tree state-clustered context-dependent hidden Markov models are used to define a set o...
Sentiment classification aims to automatically predict sentiment polarity (e.g., positive or negative) of users publishing sentiment data (e.g., reviews, blogs). Although traditio...