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128
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ICASSP
2011
IEEE
14 years 7 months ago
Outlier-aware robust clustering
Clustering is a basic task in a variety of machine learning applications. Partitioning a set of input vectors into compact, wellseparated subsets can be severely affected by the p...
Pedro A. Forero, Vassilis Kekatos, Georgios B. Gia...
IJCNN
2006
IEEE
15 years 9 months ago
Adaptation of Artificial Neural Networks Avoiding Catastrophic Forgetting
— In connectionist learning, one relevant problem is “catastrophic forgetting” that may occur when a network, trained with a large set of patterns, has to learn new input pat...
Dario Albesano, Roberto Gemello, Pietro Laface, Fr...
131
Voted
ML
2002
ACM
128views Machine Learning» more  ML 2002»
15 years 3 months ago
A Simple Method for Generating Additive Clustering Models with Limited Complexity
Additive clustering was originally developed within cognitive psychology to enable the development of featural models of human mental representation. The representational flexibili...
Michael D. Lee
147
Voted
ICML
2003
IEEE
15 years 8 months ago
An Evaluation on Feature Selection for Text Clustering
Feature selection methods have been successfully applied to text categorization but seldom applied to text clustering due to the unavailability of class label information. In this...
Tao Liu, Shengping Liu, Zheng Chen, Wei-Ying Ma
KDD
2006
ACM
180views Data Mining» more  KDD 2006»
16 years 4 months ago
Learning the unified kernel machines for classification
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang