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130
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KDD
1999
ACM
199views Data Mining» more  KDD 1999»
15 years 8 months ago
The Application of AdaBoost for Distributed, Scalable and On-Line Learning
We propose to use AdaBoost to efficiently learn classifiers over very large and possibly distributed data sets that cannot fit into main memory, as well as on-line learning wher...
Wei Fan, Salvatore J. Stolfo, Junxin Zhang
104
Voted
ECML
2006
Springer
15 years 7 months ago
Learning Process Models with Missing Data
Abstract. In this paper, we review the task of inductive process modeling, which uses domain knowledge to compose explanatory models of continuous dynamic systems. Next we discuss ...
Will Bridewell, Pat Langley, Steve Racunas, Stuart...
195
Voted
ADMI
2010
Springer
15 years 2 months ago
Real-Time Sensory Pattern Mining for Autonomous Agents
Abstract. Autonomous agents are systems situated in dynamic environments. They pursue goals and satisfy their needs by responding to external events from the environment. In these ...
Pedro Sequeira, Cláudia Antunes
125
Voted
ICML
2003
IEEE
16 years 4 months ago
Unsupervised Learning with Permuted Data
We consider the problem of unsupervised learning from a matrix of data vectors where in each row the observed values are randomly permuted in an unknown fashion. Such problems ari...
Sergey Kirshner, Sridevi Parise, Padhraic Smyth
152
Voted
FSKD
2008
Springer
174views Fuzzy Logic» more  FSKD 2008»
15 years 4 months ago
A Hybrid Re-sampling Method for SVM Learning from Imbalanced Data Sets
Support Vector Machine (SVM) has been widely studied and shown success in many application fields. However, the performance of SVM drops significantly when it is applied to the pr...
Peng Li, Pei-Li Qiao, Yuan-Chao Liu