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» An Algorithm for Learning Abductive Rules
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TJS
2010
182views more  TJS 2010»
14 years 11 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»
15 years 4 months 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
16 years 1 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 ...
151
Voted
EUROCOLT
1999
Springer
15 years 4 months 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
96
Voted
ICRA
2007
IEEE
157views Robotics» more  ICRA 2007»
15 years 6 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