Hierarchical models have been extensively studied in various domains. However, existing models assume fixed model structures or incorporate structural uncertainty generatively. In...
Recently, supervised dimensionality reduction has been gaining attention, owing to the realization that data labels are often available and indicate important underlying structure...
Background: An important step in annotation of sequenced genomes is the identification of transcription factor binding sites. More than a hundred different computational methods h...
Geir Kjetil Sandve, Osman Abul, Vegard Walseng, Fi...
We present a manifold learning approach to dimensionality
reduction that explicitly models the manifold as a mapping
from low to high dimensional space. The manifold is
represen...
— This paper describes 3D biped walking generation and control based on Limit Cycle Walking. In our study, we use the simplest possible 3D biped model with three DOFs, incorporat...
Kentaro Miyahara, Yuzuru Harada, Dragomir N. Nench...