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» The Inefficiency of Batch Training for Large Training Sets
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EUROGP
2007
Springer
126views Optimization» more  EUROGP 2007»
14 years 19 days ago
Training Binary GP Classifiers Efficiently: A Pareto-coevolutionary Approach
The conversion and extension of the Incremental Pareto-Coevolution Archive algorithm (IPCA) into the domain of Genetic Programming classification is presented. In particular, the ...
Michal Lemczyk, Malcolm I. Heywood
ICRA
2010
IEEE
158views Robotics» more  ICRA 2010»
13 years 7 months ago
Coping with imbalanced training data for improved terrain prediction in autonomous outdoor robot navigation
Abstract— Autonomous robot navigation in unstructured outdoor environments is a challenging and largely unsolved area of active research. The navigation task requires identifying...
Michael J. Procopio, Jane Mulligan, Gregory Z. Gru...
CVPR
2011
IEEE
13 years 14 days ago
Learning People Detection Models from Few Training Samples
People detection is an important task for a wide range of applications in computer vision. State-of-the-art methods learn appearance based models requiring tedious collection and ...
Leonid Pishchulin, Christian Wojek, Arjun Jain, Th...
TNN
2008
97views more  TNN 2008»
13 years 8 months ago
Training Hard-Margin Support Vector Machines Using Greedy Stagewise Algorithm
Hard-margin support vector machines (HM-SVMs) suffer from getting overfitting in the presence of noise. Soft-margin SVMs deal with this problem by introducing a regularization term...
Liefeng Bo, Ling Wang, Licheng Jiao
IJCNN
2006
IEEE
14 years 2 months ago
Divide and Conquer Strategies for MLP Training
— Over time, neural networks have proven to be extremely powerful tools for data exploration with the capability to discover previously unknown dependencies and relationships in ...
Smriti Bhagat, Dipti Deodhare