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» Using Problems to Learn Service-Oriented Computing
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113
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CEC
2005
IEEE
15 years 4 months ago
Co-evolutionary modular neural networks for automatic problem decomposition
Abstract- Decomposing a complex computational problem into sub-problems, which are computationally simpler to solve individually and which can be combined to produce a solution to ...
Vineet R. Khare, Xin Yao, Bernhard Sendhoff, Yaoch...
163
Voted
KES
2010
Springer
15 years 16 days ago
Group Formation for Collaboration in Exploratory Learning Using Group Technology Techniques
Exploratory Learning Environments (ELEs) allow learners to approach a problem in different ways; they are particularly suitable for ill-defined problems where knowledge is less str...
Mihaela Cocea, George D. Magoulas
VLSID
2005
IEEE
105views VLSI» more  VLSID 2005»
15 years 8 months ago
Placement and Routing for 3D-FPGAs Using Reinforcement Learning and Support Vector Machines
The primary advantage of using 3D-FPGA over 2D-FPGA is that the vertical stacking of active layers reduce the Manhattan distance between the components in 3D-FPGA than when placed...
R. Manimegalai, E. Siva Soumya, V. Muralidharan, B...
WMTE
2006
IEEE
15 years 8 months ago
Innovative and Sustainable Mobile Learning in Africa
Mobile learning, based on the use of mobile and wireless devices to support, enhance and deliver learning, is rapidly gaining ground as a component of blended and technology enhan...
John Traxler, Jenny Leach
GECCO
2005
Springer
108views Optimization» more  GECCO 2005»
15 years 8 months ago
Evolving recurrent models using linear GP
Turing complete Genetic Programming (GP) models introduce the concept of internal state, and therefore have the capacity for identifying interesting temporal properties. Surprisin...
Xiao Luo, Malcolm I. Heywood, A. Nur Zincir-Heywoo...