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» Evaluating learning algorithms and classifiers
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CIA
2007
Springer
14 years 3 months ago
Learning Initial Trust Among Interacting Agents
Trust learning is a crucial aspect of information exchange, negotiation, and any other kind of social interaction among autonomous agents in open systems. But most current probabil...
Achim Rettinger, Matthias Nickles, Volker Tresp
JAIR
2011
134views more  JAIR 2011»
13 years 4 months ago
Scaling up Heuristic Planning with Relational Decision Trees
Current evaluation functions for heuristic planning are expensive to compute. In numerous planning problems these functions provide good guidance to the solution, so they are wort...
Tomás de la Rosa, Sergio Jiménez, Ra...
CVPR
2010
IEEE
14 years 2 months ago
Latent Hierarchical Structural Learning for Object Detection
We present a latent hierarchical structural learning method for object detection. An object is represented by a mixture of hierarchical tree models where the nodes represent objec...
Leo Zhu, Yuanhao Chen, Antonio Torralba, Alan Yuil...
PKDD
2010
Springer
212views Data Mining» more  PKDD 2010»
13 years 7 months ago
Cross Validation Framework to Choose amongst Models and Datasets for Transfer Learning
Abstract. One solution to the lack of label problem is to exploit transfer learning, whereby one acquires knowledge from source-domains to improve the learning performance in the t...
ErHeng Zhong, Wei Fan, Qiang Yang, Olivier Versche...
TKDE
2010
182views more  TKDE 2010»
13 years 7 months ago
MILD: Multiple-Instance Learning via Disambiguation
In multiple-instance learning (MIL), an individual example is called an instance and a bag contains a single or multiple instances. The class labels available in the training set ...
Wu-Jun Li, Dit-Yan Yeung