The sequence kernel has been shown to be a promising kernel function for learning from sequential data such as speech and DNA. However, it is not scalable to massive datasets due ...
Makoto Yamada, Masashi Sugiyama, Gordon Wichern, T...
Amplitude demodulation is an ill-posed problem and so it is natural to treat it from a Bayesian viewpoint, inferring the most likely carrier and envelope under probabilistic const...
We present a new and computationally efficient scheme for classifying signals into a fixed number of known classes. We model classes as subspaces in which the corresponding data...
DIVCLUS-T is a divisive hierarchical clustering algorithm based on a monothetic bipartitional approach allowing the dendrogram of the hierarchy to be read as a decision tree. It i...
We consider the problem of transmitting data at rate over a state-dependent channel with state information available at the sender and at the same time conveying the information ab...