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PODS
2001
ACM
148views Database» more  PODS 2001»
14 years 8 months ago
On the Design and Quantification of Privacy Preserving Data Mining Algorithms
The increasing ability to track and collect large amounts of data with the use of current hardware technology has lead to an interest in the development of data mining algorithms ...
Dakshi Agrawal, Charu C. Aggarwal
KDD
2008
ACM
181views Data Mining» more  KDD 2008»
14 years 8 months ago
Learning subspace kernels for classification
Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...
ICDM
2010
IEEE
160views Data Mining» more  ICDM 2010»
13 years 6 months ago
A Privacy Preserving Framework for Gaussian Mixture Models
Abstract--This paper presents a framework for privacypreserving Gaussian Mixture Model computations. Specifically, we consider a scenario where a central service wants to learn the...
Madhusudana Shashanka
KDD
2004
ACM
196views Data Mining» more  KDD 2004»
14 years 8 months ago
Adversarial classification
Essentially all data mining algorithms assume that the datagenerating process is independent of the data miner's activities. However, in many domains, including spam detectio...
Nilesh N. Dalvi, Pedro Domingos, Mausam, Sumit K. ...
IDA
2002
Springer
13 years 8 months ago
Classification with sparse grids using simplicial basis functions
Recently we presented a new approach [20] to the classification problem arising in data mining. It is based on the regularization network approach but in contrast to other methods...
Jochen Garcke, Michael Griebel