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ICDM
2006
IEEE
91views Data Mining» more  ICDM 2006»
14 years 3 months ago
Entropy-based Concept Shift Detection
When monitoring sensory data (e.g., from a wearable device) the context oftentimes changes abruptly: people move from one situation (e.g., working quietly in their office) to ano...
Peter Vorburger, Abraham Bernstein
SIGMOD
1999
ACM
183views Database» more  SIGMOD 1999»
14 years 1 months ago
OPTICS: Ordering Points To Identify the Clustering Structure
Cluster analysis is a primary method for database mining. It is either used as a stand-alone tool to get insight into the distribution of a data set, e.g. to focus further analysi...
Mihael Ankerst, Markus M. Breunig, Hans-Peter Krie...
SDM
2008
SIAM
122views Data Mining» more  SDM 2008»
13 years 10 months ago
Type-Independent Correction of Sample Selection Bias via Structural Discovery and Re-balancing
Sample selection bias is a common problem in many real world applications, where training data are obtained under realistic constraints that make them follow a different distribut...
Jiangtao Ren, Xiaoxiao Shi, Wei Fan, Philip S. Yu
SDM
2007
SIAM
98views Data Mining» more  SDM 2007»
13 years 10 months ago
Lattice based Clustering of Temporal Gene-Expression Matrices
Individuals show different cell classes when they are in the different stages of a disease, have different disease subtypes, or have different response to a treatment or envir...
Yang Huang, Martin Farach-Colton
SDM
2007
SIAM
143views Data Mining» more  SDM 2007»
13 years 10 months ago
Less is More: Compact Matrix Decomposition for Large Sparse Graphs
Given a large sparse graph, how can we find patterns and anomalies? Several important applications can be modeled as large sparse graphs, e.g., network traffic monitoring, resea...
Jimeng Sun, Yinglian Xie, Hui Zhang, Christos Falo...
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