We propose a new transductive learning algorithm for learning optimal linear representations that utilizes unlabeled data. We pose the problem of learning linear representations a...
The Mahalanobis metric was proposed by extending the Mahalanobis distance to provide a probabilistic distance for a non-normal distribution. The Mahalanobis metric equation is a n...
Covariance matrices have recently been a popular choice for versatile tasks like recognition and tracking due to their powerful properties as local descriptor and their low comput...
This paper presents a computational framework that allows for a robust extraction of the extremal structure of scalar and vector fields on 2D manifolds embedded in 3D. This struct...
The clipping of log-likelihood ratios (LLRs) in soft demodulators for multiple-input multiple-output (MIMO) systems with bitinterleaved coded modulation (BICM) was recently observ...
Stefan Schwandter, Peter Fertl, Clemens Novak, Ger...