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1. A Study On Theory And Technique Of Geometric Modeling Based On Neural Networks And Sparse Representation
2. Research On Regularized Algorithms For Random Weights Networks
3. The Research On L1Sparse Regularization And Adaboost Algorithms For Neural Networks With Random Weights
4. Random Weights Neural Networks Based On Conjugate Gradient Method
5. A Study On Some Algorithms For Improving The Generalization Capability Of Neural Networks
6. A Study On Regularization Learning Algorithm For Noise Data
7. Research On Optimizing The Neural Network With Random Weights By Backtracking Search Algorithm And Its Application
8. Fuzziness Based Instance Selection For Supervised And Semi-Supervised Learning
9. Generalization Of Random Weights Network Based On Uncertainty
10. A Study On Regularization Algorithm Of Low Rank Matrix Recovery And Its Applications
11. Research On Active Learning Based On ELM
12. A Study On Model Optimization Of Neural Networks With Random Weights
13. Research And Application Of Interval Random Weights Neural Network
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