Manifold learning methods are promising data analysis tools. However, if we locate a new test sample on the manifold, we have to find its embedding by making use of the learned e...
The hierarchical hypercube network is suitable for massively parallel systems. An appealing property of this network is the low number of connections per processor, which can faci...
The design of software-based algorithms for fast IP address lookup targeted for general purpose processors has received tremendous attention in recent years due to its low cost im...
In this paper, we present an integrated approach to synthesis and mapping to go beyond the combinatorial limit set up by the depth-optimal FlowMap algorithm. The new algorithm, na...
Within the field of action recognition, features and descriptors are often engineered to be sparse and invariant to transformation. While sparsity makes the problem tractable, it ...