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FLAIRS
2007
15 years 1 months ago
Context-Sensitive MTL Networks for Machine Lifelong Learning
Context-sensitive Multiple Task Learning, or csMTL, is presented as a method of inductive transfer that uses a single output neural network and additional contextual inputs for le...
Daniel L. Silver, Ryan Poirier
KDD
2012
ACM
247views Data Mining» more  KDD 2012»
13 years 1 months ago
Integrating meta-path selection with user-guided object clustering in heterogeneous information networks
Real-world, multiple-typed objects are often interconnected, forming heterogeneous information networks. A major challenge for link-based clustering in such networks is its potent...
Yizhou Sun, Brandon Norick, Jiawei Han, Xifeng Yan...
IJCNN
2007
IEEE
15 years 5 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
ICML
2005
IEEE
15 years 11 months ago
Learning the structure of Markov logic networks
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. In this pap...
Stanley Kok, Pedro Domingos
104
Voted
ECAI
2000
Springer
15 years 2 months ago
Learning Efficiently with Neural Networks: A Theoretical Comparison between Structured and Flat Representations
Abstract. We are interested in the relationship between learning efficiency and representation in the case of supervised neural networks for pattern classification trained by conti...
Marco Gori, Paolo Frasconi, Alessandro Sperduti