We claim and present arguments to the effect that a large class of manifold learning algorithms that are essentially local and can be framed as kernel learning algorithms will suf...
This study explores manifold representations of emotionally modulated speech. The manifolds are derived in the articulatory space and two acoustic spaces (MFB and MFCC) using isom...
Abstract. In this paper we elaborate on the challenges of learning manifolds that have many relevant clusters, and where the clusters can have widely varying statistics. We call su...
This paper gives a definition of Hierarchical Spatial Reasoning, which computes increasingly better results in a hierarchical fashion and stops the computation when a result is ac...