We present an algorithmic framework for supervised classification learning where the set of labels is organized in a predefined hierarchical structure. This structure is encoded b...
We present a method for detecting and parsing buildings from unorganized 3D point clouds into a compact, hierarchical representation that is useful for high-level tasks. The input...
Clustering, or unsupervised classification, has many uses in fields that depend on grouping results from large amount of data, an example being the N-body cosmological simulation ...
In this paper, we examine the problem of large-volume data dissemination via overlay networks. A natural way to maximize the throughput of an overlay multicast session is to split...
Hierarchies are an intuitive and effective organization paradigm for data. Of late there has been considerable research on automatically learning hierarchical organizations of dat...