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Chapter
Deep Learning via Semi-supervised Embedding
We show how nonlinear semi-supervised embedding algorithms popular for use with “shallow” learning techniques such as kernel methods can be easily applied to deep multi-layer architectures, either as a regular...
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Chapter and Conference Paper
Learning Manifolds in Forensic Data
Chemical data related to illicit cocaine seizures is analyzed using linear and nonlinear dimensionality reduction methods. The goal is to find relevant features that could guide the data analysis process in ch...
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Chapter and Conference Paper
Multi-objective Optimization of a Composite Material Spring Design Using an Evolutionary Algorithm
A multi-objective evolutionary algorithm is applied to optimize the design of a helical spring made out of a composite material. The criteria considered are the minimization of the mass along with the maximiza...