As the Internet population grows, not only computers but household electric appliances, such as VCRs and a refrigerators, will become connected to a network. The demand of connecti...
We investigate the application of a low-cost, pervasively distributed network to plan paths for mobile robots in environments with dynamic obstacles. We consider a heterogeneous s...
In this paper, we present advanced algorithms to reduce the computation cost of block matching algorithms for motion estimation in video coding. Advanced Multilevel Successive Elim...
We propose a novel method for approximate inference in Bayesian networks (BNs). The idea is to sample data from a BN, learn a latent tree model (LTM) from the data offline, and wh...
Automated generators for synthetic models and data can play a crucial role in designing new algorithms/modelframeworks, given the sparsity of benchmark models for empirical analys...