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DMSN
2006
ACM
16 years 19 days ago
Intelligent system monitoring on large clusters
Modern data centers have a large number of components that must be monitored, including servers, switches/routers, and environmental control systems. This paper describes InteMon,...
Jimeng Sun, Evan Hoke, John D. Strunk, Gregory R. ...
ICDM
2008
IEEE
90views Data Mining» more  ICDM 2008»
16 years 1 months ago
Finding Alternative Clusterings Using Constraints
1 The aim of data mining is to find novel and actionable insights. However, most algorithms typically just find a single explanation of the data even though alternatives could e...
Ian Davidson, Zijie Qi
176
Voted
KDD
2008
ACM
119views Data Mining» more  KDD 2008»
16 years 7 months ago
SAIL: summation-based incremental learning for information-theoretic clustering
Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
Junjie Wu, Hui Xiong, Jian Chen
ISNN
2011
Springer
14 years 9 months ago
Orthogonal Feature Learning for Time Series Clustering
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
Xiaozhe Wang, Leo Lopes
CAV
2009
Springer
171views Hardware» more  CAV 2009»
16 years 7 months ago
CalFuzzer: An Extensible Active Testing Framework for Concurrent Programs
Active testing has recently been introduced to effectively test concurrent programs. Active testing works in two phases. It first uses predictive off-the-shelf static or dynamic pr...
Pallavi Joshi, Mayur Naik, Chang-Seo Park, Koushik...