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AAAI
2000
13 years 9 months ago
A Unified Bias-Variance Decomposition for Zero-One and Squared Loss
The bias-variance decomposition is a very useful and widely-used tool for understanding machine-learning algorithms. It was originally developed for squared loss. In recent years,...
Pedro Domingos
IJCAI
1997
13 years 9 months ago
On the Role of Hierarchy for Neural Network Interpretation
In this paper, we concentrate on the expressive power of hierarchical structures in neural networks. Recently, the so-called SplitNet model was introduced. It develops a dynamic n...
Jürgen Rahmel, Christian Blum, Peter Hahn
UAI
1993
13 years 9 months ago
Probabilistic Assumption-Based Reasoning
In this paper the classical propositional assumption-based model is extended to incorporate probabilities for the assumptions. Then the whole model is placed into the framework of...
Jürg Kohlas, Paul-André Monney
GIR
2008
ACM
13 years 9 months ago
Map-based vs. knowledge-based toponym disambiguation
Toponym Disambiguation, i.e. the task of assigning to place name their correct reference in the world, is getting more attention from many researchers. Many methods have been prop...
Davide Buscaldi, Paolo Rosso
CCGRID
2010
IEEE
13 years 8 months ago
Gridifying a Diffusion Tensor Imaging Analysis Pipeline
—Diffusion Tensor MRI (DTI) is a rather recent image acquisition modality that can help identify disease processes in nerve bundles in the brain. Due to the large and complex nat...
Matthan W. A. Caan, Frans M. Vos, Antoine H. C. va...