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» An Algorithm for Learning Abductive Rules
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TJS
2010
182views more  TJS 2010»
13 years 6 months ago
A novel unsupervised classification approach for network anomaly detection by k-Means clustering and ID3 decision tree learning
This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...
Yasser Yasami, Saadat Pour Mozaffari
VLDB
1998
ACM
147views Database» more  VLDB 1998»
14 years 8 days ago
Scalable Techniques for Mining Causal Structures
Mining for association rules in market basket data has proved a fruitful areaof research. Measures such as conditional probability (confidence) and correlation have been used to i...
Craig Silverstein, Sergey Brin, Rajeev Motwani, Je...
ICML
2008
IEEE
14 years 8 months ago
Boosting with incomplete information
In real-world machine learning problems, it is very common that part of the input feature vector is incomplete: either not available, missing, or corrupted. In this paper, we pres...
Feng Jiao, Gholamreza Haffari, Greg Mori, Shaojun ...
EUROCOLT
1999
Springer
14 years 10 days ago
Averaging Expert Predictions
We consider algorithms for combining advice from a set of experts. In each trial, the algorithm receives the predictions of the experts and produces its own prediction. A loss func...
Jyrki Kivinen, Manfred K. Warmuth
ICRA
2007
IEEE
157views Robotics» more  ICRA 2007»
14 years 2 months ago
Learning to Select State Machines using Expert Advice on an Autonomous Robot
— Hierarchical state machines have proven to be a powerful tool for controlling autonomous robots due to their flexibility and modularity. For most real robot implementations, h...
Brenna Argall, Brett Browning, Manuela M. Veloso