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ECML
2007
Springer
16 years 1 months ago
Learning an Outlier-Robust Kalman Filter
We introduce a modified Kalman filter that performs robust, real-time outlier detection, without the need for manual parameter tuning by the user. Systems that rely on high quali...
Jo-Anne Ting, Evangelos Theodorou, Stefan Schaal
MCS
2007
Springer
16 years 1 months ago
An Ensemble Approach for Incremental Learning in Nonstationary Environments
Abstract. We describe an ensemble of classifiers based algorithm for incremental learning in nonstationary environments. In this formulation, we assume that the learner is presente...
Michael Muhlbaier, Robi Polikar
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
ICTAI
2006
IEEE
16 years 1 months ago
Learning to Predict Salient Regions from Disjoint and Skewed Training Sets
We present an ensemble learning approach that achieves accurate predictions from arbitrarily partitioned data. The partitions come from the distributed processing requirements of ...
Larry Shoemaker, Robert E. Banfield, Lawrence O. H...
SIGCSE
2006
ACM
201views Education» more  SIGCSE 2006»
16 years 1 months ago
Everything I needed to know about teaching I learned in kindergarten: bringing elementary education techniques to undergraduate
By expanding the teaching styles used in computer science classrooms, we can expand the audience of students that enjoy and excel in technology. Rather than focusing on major curr...
Shannon Pollard, Robert C. Duvall