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» A Failure to Learn from the Past
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IDA
2009
Springer
15 years 4 months ago
Estimating Markov Random Field Potentials for Natural Images
Markov Random Field (MRF) models with potentials learned from the data have recently received attention for learning the low-level structure of natural images. A MRF provides a pri...
Urs Köster, Jussi T. Lindgren, Aapo Hyvä...
ESANN
2008
14 years 11 months ago
Learning Inverse Dynamics: a Comparison
While it is well-known that model can enhance the control performance in terms of precision or energy efficiency, the practical application has often been limited by the complexiti...
Duy Nguyen-Tuong, Jan Peters, Matthias Seeger, Ber...
ATAL
2008
Springer
14 years 11 months ago
A statistical relational model for trust learning
We address the learning of trust based on past observations and context information. We argue that from the truster's point of view trust is best expressed as one of several ...
Achim Rettinger, Matthias Nickles, Volker Tresp
IPMI
2005
Springer
15 years 10 months ago
Segmenting and Tracking the Left Ventricle by Learning the Dynamics in Cardiac Images
Having accurate left ventricle (LV) segmentations across a cardiac cycle provides useful quantitative (e.g. ejection fraction) and qualitative information for diagnosis of certain ...
Alan S. Willsky, Godtfred Holmvang, Müjdat &C...
ML
2000
ACM
105views Machine Learning» more  ML 2000»
14 years 9 months ago
Multiple Comparisons in Induction Algorithms
Abstract. A single mechanism is responsible for three pathologies of induction algorithms: attribute selection errors, overfitting, and oversearching. In each pathology, induction ...
David D. Jensen, Paul R. Cohen