Convolution kernels, constructed by convolution of sub-kernels defined on sub-structures of composite objects, are widely used in classification, where one important issue is to ch...
Recent work shows that Support vector machines (SVMs) can be solved efficiently in the primal. This paper follows this line of research and shows how to build sparse support vector...
In this paper, we study the privacy-preserving decision tree building problem on vertically partitioned data. We made two contributions. First, we propose a novel hybrid approach, ...
Abstract. Noise significantly affects cluster quality. Conventional clustering methods hardly detect clusters in a data set containing a large amount of noise. Projected clusterin...
Jiuyong Li, Xiaodi Huang, Clinton Selke, Jianming ...
Distance-preserving projection based perturbation has gained much attention in privacy-preserving data mining in recent years since it mitigates the privacy/accuracy tradeoff by ac...
The co-association (CA) matrix was previously introduced to combine multiple partitions. In this paper, we analyze the CA matrix, and address its difference from the similarity ma...
In graph mining applications, there has been an increasingly strong urge for imposing user-specified constraints on the mining results. However, unlike most traditional itemset co...
Abstract. We study the problem of mining frequent itemsets from uncertain data under a probabilistic framework. We consider transactions whose items are associated with existential...