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ICDM
2006
IEEE
92views Data Mining» more  ICDM 2006»
14 years 1 months ago
Window-based Tensor Analysis on High-dimensional and Multi-aspect Streams
Data stream values are often associated with multiple aspects. For example, each value from environmental sensors may have an associated type (e.g., temperature, humidity, etc) as...
Jimeng Sun, Spiros Papadimitriou, Philip S. Yu
ICDM
2005
IEEE
137views Data Mining» more  ICDM 2005»
14 years 1 months ago
Leveraging Relational Autocorrelation with Latent Group Models
The presence of autocorrelation provides a strong motivation for using relational learning and inference techniques. Autocorrelation is a statistical dependence between the values...
Jennifer Neville, David Jensen
PKDD
2001
Springer
104views Data Mining» more  PKDD 2001»
14 years 3 days ago
Data Reduction Using Multiple Models Integration
Large amount of available information does not necessarily imply that induction algorithms must use all this information. Samples often provide the same accuracy with less computat...
Aleksandar Lazarevic, Zoran Obradovic
KDD
2010
ACM
224views Data Mining» more  KDD 2010»
13 years 11 months ago
Multi-label learning by exploiting label dependency
In multi-label learning, each training example is associated with a set of labels and the task is to predict the proper label set for the unseen example. Due to the tremendous (ex...
Min-Ling Zhang, Kun Zhang
SDM
2010
SIAM
156views Data Mining» more  SDM 2010»
13 years 9 months ago
Co-selection of Features and Instances for Unsupervised Rare Category Analysis
Rare category analysis is of key importance both in theory and in practice. Previous research work focuses on supervised rare category analysis, such as rare category detection an...
Jingrui He, Jaime G. Carbonell