When given a small sample, we show that classification with SVM can be considerably enhanced by using a kernel function learned from the training data prior to discrimination. Thi...
Clustering is the problem of identifying the distribution of patterns and intrinsic correlations in large data sets by partitioning the data points into similarity classes. This p...
Abstract: Current peer-to-peer systems are network-agnostic, often generating large volumes of unnecessary inter-ISP traffic. Although recent work has shown the benefits of ISP-a...
Co-clustering has emerged as an important technique for mining contingency data matrices. However, almost all existing coclustering algorithms are hard partitioning, assigning each...
Outlier analysis is an important task in data mining and has attracted much attention in both research and applications. Previous work on outlier detection involves different type...
Wen Jin, Yuelong Jiang, Weining Qian, Anthony K. H...