Many important problems involve clustering large datasets. Although naive implementations of clustering are computationally expensive, there are established efficient techniques f...
In this paper, we propose a model for representing and predicting distances in large-scale networks by matrix factorization. The model is useful for network distance sensitive app...
Internet distance prediction gives pair-wise latency information with limited measurements. Recent studies have revealed that the quality of existing prediction mechanisms from th...
Rongmei Zhang, Y. Charlie Hu, Xiaojun Lin, Sonia F...
For almost a decade, Content-Based Image Retrieval has been an active research area, yet one fundamental problem remains largely unsolved: how to measure perceptual similarity. To...
This paper presents a partitional dynamic clustering method for interval data based on adaptive Hausdorff distances. Dynamic clustering algorithms are iterative two-step relocatio...
Francisco de A. T. de Carvalho, Renata M. C. R. de...