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TNN
2010
234views Management» more  TNN 2010»
13 years 2 months ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes
WWW
2010
ACM
14 years 2 months ago
Factorizing personalized Markov chains for next-basket recommendation
Recommender systems are an important component of many websites. Two of the most popular approaches are based on matrix factorization (MF) and Markov chains (MC). MF methods learn...
Steffen Rendle, Christoph Freudenthaler, Lars Schm...
AAAI
1994
13 years 9 months ago
Solution Reuse in Dynamic Constraint Satisfaction Problems
Many AI problems can be modeled as constraint satisfaction problems (CSP), but many of them are actually dynamic: the set of constraints to consider evolves because of the environ...
Gérard Verfaillie, Thomas Schiex
ECAL
2007
Springer
13 years 11 months ago
Genotype Reuse More Important than Genotype Size in Evolvability of Embodied Neural Networks
odel of Embodiment on Abstract Systems: from Hierarchy to Heterarchy Kohei Nakajima, Soya Shinkai, Takashi Ikegami A Behavior-Based Model of the Hydra, Phylum Cnidaria Malin Aktius...
Chad W. Seys, Randall D. Beer
IADIS
2003
13 years 9 months ago
Versioning of E-Learning Objects Enabling Flexible Reuse
One promise that has always been made in the field of e-learning is the possibility to create and deliver learning material that is adaptable to individual learners. Realising thi...
Wolfgang Theilmann, Michael Altenhofen