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ESANN
2007
15 years 5 months ago
How to process uncertainty in machine learning?
Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
Barbara Hammer, Thomas Villmann
CN
2008
106views more  CN 2008»
15 years 4 months ago
Efficient virtual-backbone routing in mobile ad hoc networks
Since the physical topology of Mobile Ad hoc Networks (MANETs) is generally unstable, an appealing approach is the construction of a stable and robust virtual topology or backbone...
Jamal N. Al-Karaki, Ahmed E. Kamal
ML
2000
ACM
15 years 3 months ago
Maximizing Theory Accuracy Through Selective Reinterpretation
Existing methods for exploiting awed domain theories depend on the use of a su ciently large set of training examples for diagnosing and repairing aws in the theory. In this paper,...
Shlomo Argamon-Engelson, Moshe Koppel, Hillel Walt...
ATAL
2007
Springer
15 years 10 months ago
Conditional random fields for activity recognition
Activity recognition is a key component for creating intelligent, multi-agent systems. Intrinsically, activity recognition is a temporal classification problem. In this paper, we...
Douglas L. Vail, Manuela M. Veloso, John D. Laffer...
CIKM
2009
Springer
15 years 8 months ago
Improving binary classification on text problems using differential word features
We describe an efficient technique to weigh word-based features in binary classification tasks and show that it significantly improves classification accuracy on a range of proble...
Justin Martineau, Tim Finin, Anupam Joshi, Shamit ...