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» Probabilistic frameworks for privacy-aware data mining
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ICDM
2009
IEEE
163views Data Mining» more  ICDM 2009»
14 years 3 months ago
Kernel Conditional Quantile Estimation via Reduction Revisited
Quantile regression refers to the process of estimating the quantiles of a conditional distribution and has many important applications within econometrics and data mining, among ...
Novi Quadrianto, Kristian Kersting, Mark D. Reid, ...
SDM
2009
SIAM
144views Data Mining» more  SDM 2009»
14 years 5 months ago
On Segment-Based Stream Modeling and Its Applications.
The primary constraint in the effective mining of data streams is the large volume of data which must be processed in real time. In many cases, it is desirable to store a summary...
Charu C. Aggarwal
CIKM
2010
Springer
13 years 7 months ago
FacetCube: a framework of incorporating prior knowledge into non-negative tensor factorization
Non-negative tensor factorization (NTF) is a relatively new technique that has been successfully used to extract significant characteristics from polyadic data, such as data in s...
Yun Chi, Shenghuo Zhu
ICDM
2005
IEEE
109views Data Mining» more  ICDM 2005»
14 years 2 months ago
Triple Jump Acceleration for the EM Algorithm
This paper presents the triple jump framework for accelerating the EM algorithm and other bound optimization methods. The idea is to extrapolate the third search point based on th...
Han-Shen Huang, Bou-Ho Yang, Chun-Nan Hsu
ICDE
2009
IEEE
1081views Database» more  ICDE 2009»
15 years 8 months ago
Modeling and Integrating Background Knowledge in Data Anonymization
Recent work has shown the importance of considering the adversary’s background knowledge when reasoning about privacy in data publishing. However, it is very difficult for the d...
Tiancheng Li, Ninghui Li, Jian Zhang