A trajectory is the time-stamped path of a moving entity through space. Given a set of trajectories, this paper proposes new conceptual definitions for a spatio-temporal pattern n...
Manifold learning can discover the structure of high dimensional data and provides understanding of multidimensional patterns by preserving the local geometric characteristics. Ho...
We present a probabilistic model for clustering of objects represented via pairwise dissimilarities. We propose that even if an underlying vectorial representation exists, it is b...
Julia E. Vogt, Sandhya Prabhakaran, Thomas J. Fuch...
We propose an ℓ1 criterion for dictionary learning for sparse signal representation. Instead of directly searching for the dictionary vectors, our dictionary learning approach i...
The complexity of sphere decoding (SD) has been widely studied due to the importance of this algorithm in obtaining the optimal Maximum Likelihood (ML) performance with lower compl...