Probabilistic models have been previously shown to be efficient and effective for modeling and recognition of human motion. In particular we focus on methods which represent the h...
We introduce a new graph-theoretic approach to image segmentation based on minimizing a novel class of `mean cut' cost functions. Minimizing these cost functions corresponds ...
Garbage collectors are notoriously hard to verify, due to their lowlevel interaction with the underlying system and the general difficulty in reasoning about reachability in graph...
In this paper, we present a novel feature extraction framework, called learning by propagability. The whole learning process is driven by the philosophy that the data labels and o...
Bingbing Ni, Shuicheng Yan, Ashraf A. Kassim, Loon...
Distributed Hash Tables (DHT) algorithms obtain good lookup performance bounds by using deterministic rules to organize peer nodes into an overlay network. To preserve the invaria...