Clustering large data sets with high dimensionality is a challenging data-mining task. This paper presents a framework to perform such a task efficiently. It is based on the notio...
Ying Lai, Ratko Orlandic, Wai Gen Yee, Sachin Kulk...
We propose DHCS, a method of distributed, hierarchical clustering and summarization for online data analysis and mining in sensor networks. Different from the acquisition and aggre...
Wavelet methods for geometry encoding is a recently emerged superset of multiresolution analysis which has proven to be very efficient in term of compression and adaptive transmis...
The Bidirectional Texture Function (BTF) is becoming widely used for accurate representation of real-world material appearance. In this paper a novel BTF compression model is prop...
This work examines under what conditions compression methodologies can retain the outcome of clustering operations. We focus on the popular k-Means clustering algorithm and we dem...
Deepak S. Turaga, Michail Vlachos, Olivier Versche...