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IPM
2006
64views more  IPM 2006»
13 years 10 months ago
Text mining without document context
We consider a challenging clustering task: the clustering of muti-word terms without document co-occurrence information in order to form coherent groups of topics. For this task, ...
Eric SanJuan, Fidelia Ibekwe-Sanjuan
NPL
2006
172views more  NPL 2006»
13 years 10 months ago
Adapting RBF Neural Networks to Multi-Instance Learning
In multi-instance learning, the training examples are bags composed of instances without labels, and the task is to predict the labels of unseen bags through analyzing the training...
Min-Ling Zhang, Zhi-Hua Zhou
ICML
2001
IEEE
14 years 11 months ago
Some Theoretical Aspects of Boosting in the Presence of Noisy Data
This is a survey of some theoretical results on boosting obtained from an analogous treatment of some regression and classi cation boosting algorithms. Some related papers include...
Wenxin Jiang
ICDM
2010
IEEE
135views Data Mining» more  ICDM 2010»
13 years 8 months ago
Learning a Bi-Stochastic Data Similarity Matrix
An idealized clustering algorithm seeks to learn a cluster-adjacency matrix such that, if two data points belong to the same cluster, the corresponding entry would be 1; otherwise ...
Fei Wang, Ping Li, Arnd Christian König
CORR
2000
Springer
84views Education» more  CORR 2000»
13 years 10 months ago
Robust Classification for Imprecise Environments
In real-world environments it usually is difficult to specify target operating conditions precisely, for example, target misclassification costs. This uncertainty makes building ro...
Foster J. Provost, Tom Fawcett