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GECCO
2009
Springer
110views Optimization» more  GECCO 2009»
15 years 11 months ago
EMO shines a light on the holes of complexity space
Typical domains used in machine learning analyses only partially cover the complexity space, remaining a large proportion of problem difficulties that are not tested. Since the ac...
Núria Macià, Albert Orriols-Puig, Es...
ECML
1993
Springer
15 years 10 months ago
Complexity Dimensions and Learnability
In machine learning theory, problem classes are distinguished because of di erences in complexity. In 6 , a stochastic model of learning from examples was introduced. This PAClear...
Shan-Hwei Nienhuys-Cheng, Mark Polman
CVPR
2005
IEEE
15 years 8 months ago
Database-Guided Segmentation of Anatomical Structures with Complex Appearance
The segmentation of anatomical structures has been traditionally formulated as a perceptual grouping task, and solved through clustering and variational approaches. However, such ...
Bogdan Georgescu, Xiang Sean Zhou, Dorin Comaniciu...
IJCNN
2000
IEEE
15 years 10 months ago
Storage and Recall of Complex Temporal Sequences through a Contextually Guided Self-Organizing Neural Network
A self-organizing neural network for learning and recall of complex temporal sequences is proposed. we consider a single sequence with repeated items, or several sequences with a c...
Guilherme De A. Barreto, Aluizio F. R. Araú...
IJCNN
2000
IEEE
15 years 9 months ago
Unsupervised Classification of Complex Clusters in Networks of Spiking Neurons
For unsupervised clustering in a network of spiking neurons we develop a temporal encoding of continuously valued data to obtain arbitrary clustering capacity and precision with a...
Sander M. Bohte, Johannes A. La Poutré, Joo...