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» Phenomenal Data Mining: From Data to Phenomena
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SDM
2010
SIAM
200views Data Mining» more  SDM 2010»
15 years 3 months ago
Residual Bayesian Co-clustering for Matrix Approximation
In recent years, matrix approximation for missing value prediction has emerged as an important problem in a variety of domains such as recommendation systems, e-commerce and onlin...
Hanhuai Shan, Arindam Banerjee
SDM
2008
SIAM
134views Data Mining» more  SDM 2008»
15 years 3 months ago
Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation
Covariate shift is a situation in supervised learning where training and test inputs follow different distributions even though the functional relation remains unchanged. A common...
Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Steffen...
SDM
2008
SIAM
150views Data Mining» more  SDM 2008»
15 years 3 months ago
A Stagewise Least Square Loss Function for Classification
This paper presents a stagewise least square (SLS) loss function for classification. It uses a least square form within each stage to approximate a bounded monotonic nonconvex los...
Shuang-Hong Yang, Bao-Gang Hu
SDM
2008
SIAM
129views Data Mining» more  SDM 2008»
15 years 3 months ago
Statistical Density Prediction in Traffic Networks
Recently, modern tracking methods started to allow capturing the position of massive numbers of moving objects. Given this information, it is possible to analyze and predict the t...
Hans-Peter Kriegel, Matthias Renz, Matthias Schube...
SDM
2008
SIAM
140views Data Mining» more  SDM 2008»
15 years 3 months ago
Creating a Cluster Hierarchy under Constraints of a Partially Known Hierarchy
Although clustering under constraints is a current research topic, a hierarchical setting, in which a hierarchy of clusters is the goal, is usually not considered. This paper trie...
Korinna Bade, Andreas Nürnberger