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ICDM
2010
IEEE
228views Data Mining» more  ICDM 2010»
15 years 1 months ago
Active Learning from Multiple Noisy Labelers with Varied Costs
In active learning, where a learning algorithm has to purchase the labels of its training examples, it is often assumed that there is only one labeler available to label examples, ...
Yaling Zheng, Stephen D. Scott, Kun Deng
ICDM
2006
IEEE
84views Data Mining» more  ICDM 2006»
15 years 10 months ago
Exploratory Under-Sampling for Class-Imbalance Learning
Under-sampling is a class-imbalance learning method which uses only a subset of major class examples and thus is very efficient. The main deficiency is that many major class exa...
Xu-Ying Liu, Jianxin Wu, Zhi-Hua Zhou
ICDM
2002
IEEE
105views Data Mining» more  ICDM 2002»
15 years 9 months ago
Empirical Comparison of Various Reinforcement Learning Strategies for Sequential Targeted Marketing
We empirically evaluate the performance of various reinforcement learning methods in applications to sequential targeted marketing. In particular, we propose and evaluate a progre...
Naoki Abe, Edwin P. D. Pednault, Haixun Wang, Bian...
IDEAL
2009
Springer
15 years 11 months ago
Improving the Language Active Learning with Multiagent Systems
Nowadays, there is a growing need for providing novel solutions to facilitate active learning in dependency environments. This paper present a multiagent architecture that incorpor...
Cristian Pinzón, Vivian López, Javie...
KDD
2002
ACM
179views Data Mining» more  KDD 2002»
16 years 4 months ago
From Data To Insight: The Community Of Multimedia Agents
Multimedia Data Mining requires the ability to automatically analyze and understand the content. The Community of Multimedia Agents project (COMMA) is devoted to creating an open ...
Gang Wei, Valery A. Petrushin, Anatole Gershman