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» Learning Instance-Specific Predictive Models
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ICST
2009
IEEE
14 years 3 months ago
A Model Building Process for Identifying Actionable Static Analysis Alerts
Automated static analysis can identify potential source code anomalies early in the software process that could lead to field failures. However, only a small portion of static ana...
Sarah Smith Heckman, Laurie A. Williams
KDD
2008
ACM
137views Data Mining» more  KDD 2008»
14 years 9 months ago
Learning classifiers from only positive and unlabeled data
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Charles Elkan, Keith Noto
COGSR
2011
109views more  COGSR 2011»
13 years 3 months ago
How groups develop a specialized domain vocabulary: A cognitive multi-agent model
We simulate the evolution of a domain vocabulary in small communities. Empirical data show that human communicators can evolve graphical languages quickly in a constrained task (P...
David Reitter, Christian Lebiere
PKDD
2009
Springer
152views Data Mining» more  PKDD 2009»
14 years 3 months ago
Feature Selection for Value Function Approximation Using Bayesian Model Selection
Abstract. Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of th...
Tobias Jung, Peter Stone
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
14 years 9 months ago
Effective multi-label active learning for text classification
Labeling text data is quite time-consuming but essential for automatic text classification. Especially, manually creating multiple labels for each document may become impractical ...
Bishan Yang, Jian-Tao Sun, Tengjiao Wang, Zheng Ch...