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» Learning relational dependency networks in hybrid domains
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IJCAI
2001
15 years 2 months ago
Probabilistic Classification and Clustering in Relational Data
Supervised and unsupervised learning methods have traditionally focused on data consisting of independent instances of a single type. However, many real-world domains are best des...
Benjamin Taskar, Eran Segal, Daphne Koller
TNN
1998
146views more  TNN 1998»
15 years 11 days ago
Fuzzy lattice neural network (FLNN): a hybrid model for learning
— This paper proposes two hierarchical schemes for learning, one for clustering and the other for classification problems. Both schemes can be implemented on a fuzzy lattice neu...
Vassilios Petridis, Vassilis G. Kaburlasos
101
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IJCNN
2007
IEEE
15 years 7 months ago
Encoding Complete Body Models Enables Task Dependent Optimal Behavior
— Many neural network models of (human) motor learning focus on the acquisition of direct goal-to-action mappings, which results in rather inflexible motor control programs. We ...
Oliver Herbort, Martin V. Butz
AAAI
2006
15 years 2 months ago
Cross-Domain Knowledge Transfer Using Structured Representations
Previous work in knowledge transfer in machine learning has been restricted to tasks in a single domain. However, evidence from psychology and neuroscience suggests that humans ar...
Samarth Swarup, Sylvian R. Ray
ICML
2005
IEEE
16 years 1 months ago
Dirichlet enhanced relational learning
We apply nonparametric hierarchical Bayesian modelling to relational learning. In a hierarchical Bayesian approach, model parameters can be "personalized", i.e., owned b...
Zhao Xu, Volker Tresp, Kai Yu, Shipeng Yu, Hans-Pe...