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» Making inferences with small numbers of training sets
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ICML
2007
IEEE
14 years 8 months ago
Minimum reference set based feature selection for small sample classifications
We address feature selection problems for classification of small samples and high dimensionality. A practical example is microarray-based cancer classification problems, where sa...
Xue-wen Chen, Jong Cheol Jeong
ICAI
2008
13 years 9 months ago
Mapping of Activity Recognition as a Distributed Inference Problem in Sensor Network
- This paper presents a distributed model for detecting Activities of Daily Living (ADLs) in a home setting. We consider an environment where household devices and utensils are aug...
Md. Kamrul Hasan, Husne Ara Rubaiyeat, Young-Koo L...
COLT
2001
Springer
14 years 2 days ago
Tracking a Small Set of Experts by Mixing Past Posteriors
In this paper, we examine on-line learning problems in which the target concept is allowed to change over time. In each trial a master algorithm receives predictions from a large ...
Olivier Bousquet, Manfred K. Warmuth
ICDM
2008
IEEE
172views Data Mining» more  ICDM 2008»
14 years 2 months ago
Active Learning of Equivalence Relations by Minimizing the Expected Loss Using Constraint Inference
Selecting promising queries is the key to effective active learning. In this paper, we investigate selection techniques for the task of learning an equivalence relation where the ...
Steffen Rendle, Lars Schmidt-Thieme
SP
2008
IEEE
176views Security Privacy» more  SP 2008»
14 years 1 months ago
Casting out Demons: Sanitizing Training Data for Anomaly Sensors
The efficacy of Anomaly Detection (AD) sensors depends heavily on the quality of the data used to train them. Artificial or contrived training data may not provide a realistic v...
Gabriela F. Cretu, Angelos Stavrou, Michael E. Loc...