The paper presents a comparative analysis of data harvesting and distributed computing as complementary models of service delivery within large-scale federated digital libraries. I...
Multi-instance (MI) learning is a variant of supervised learning where labeled examples consist of bags (i.e. multi-sets) of feature vectors instead of just a single feature vecto...
With the increased popularity of replica-based services in distributed systems such as the Grid, consistency control among replicas becomes more and more important. To this end, I...
: The traditional latent class analysis (LCA) uses a mixture model with binary responses on each subject that are independent conditional on cluster membership. However, in many pr...
Co-clustering has emerged as an important technique for mining contingency data matrices. However, almost all existing coclustering algorithms are hard partitioning, assigning each...