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141
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SAB
2010
Springer
117views Optimization» more  SAB 2010»
15 years 1 months ago
Indirectly Encoding Neural Plasticity as a Pattern of Local Rules
Biological brains can adapt and learn from past experience. In neuroevolution, i.e. evolving artificial neural networks (ANNs), one way that agents controlled by ANNs can evolve t...
Sebastian Risi, Kenneth O. Stanley
133
Voted
STAIRS
2008
109views Education» more  STAIRS 2008»
15 years 4 months ago
Representing Case Variations for Learning General and Specific Adaptation Rules
Adaptation is a task of case-based reasoning systems that is largely domain-dependant. This motivates the study of adaptation knowledge acquisition (AKA) that can be carried out th...
Fadi Badra, Jean Lieber
122
Voted
ICML
2010
IEEE
15 years 4 months ago
Learning Deep Boltzmann Machines using Adaptive MCMC
When modeling high-dimensional richly structured data, it is often the case that the distribution defined by the Deep Boltzmann Machine (DBM) has a rough energy landscape with man...
Ruslan Salakhutdinov
130
Voted
AH
2006
Springer
15 years 5 months ago
Dynamic Content Discovery, Harvesting and Delivery, from Open Corpus Sources, for Adaptive Systems
Personalised elearning is being heralded as one of the grand challenges of next generation learning systems, in particular, its ability to support greater effectiveness, efficiency...
Séamus Lawless, Vincent Wade
123
Voted
AH
2006
Springer
15 years 7 months ago
A Unified Approach to Adaptive Hypermedia Personalisation and Adaptive Service Composition
Adaptive Hypermedia is utilised in several domains, such as eLearning and professional training, where there is a growing movement towards the use of cognitively richer and more `a...
Ian O'Keeffe, Owen Conlan, Vincent Wade