In this work, a generalized method for learning from sequence of unlabelled data points based on unsupervised order-preserving regression is proposed. Sequence learning is a funda...
This paper explores a recently proposed and rarely reported subspace learning method, Spectral Regression Discriminant Analysis (SRDA) [1, 2], on silhouette based human action rec...
We explore generic mechanisms to introduce structural hints into the method of Unsupervised Kernel Regression (UKR) in order to learn representations of data sequences in a semi-su...
Jan Steffen, Stefan Klanke, Sethu Vijayakumar, Hel...
We study the problem of discovering a manifold that best preserves information relevant to a nonlinear regression. Solving this problem involves extending and uniting two threads ...
Training principles for unsupervised learning are often derived from motivations that appear to be independent of supervised learning. In this paper we present a simple unificatio...