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ICDM
2006
IEEE
84views Data Mining» more  ICDM 2006»
16 years 1 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
ECML
2003
Springer
16 years 14 days ago
Robust k-DNF Learning via Inductive Belief Merging
A central issue in logical concept induction is the prospect of inconsistency. This problem may arise due to noise in the training data, or because the target concept does not fit...
Frédéric Koriche, Joël Quinquet...
ATAL
2007
Springer
15 years 11 months ago
On discovery and learning of models with predictive representations of state for agents with continuous actions and observations
Models of agent-environment interaction that use predictive state representations (PSRs) have mainly focused on the case of discrete observations and actions. The theory of discre...
David Wingate, Satinder P. Singh
ECAI
2006
Springer
15 years 11 months ago
Least Squares SVM for Least Squares TD Learning
Abstract. We formulate the problem of least squares temporal difference learning (LSTD) in the framework of least squares SVM (LS-SVM). To cope with the large amount (and possible ...
Tobias Jung, Daniel Polani
ECCV
2006
Springer
15 years 11 months ago
Learning Semantic Scene Models by Trajectory Analysis
Abstract. In this paper, we describe an unsupervised learning framework to segment a scene into semantic regions and to build semantic scene models from longterm observations of mo...
Xiaogang Wang, Kinh Tieu, Eric Grimson