4 Result(s)
within
Frédéric Ratle
Algorithm Analysis and Problem Complexity
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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
Large-Scale Clustering through Functional Embedding
We present a new framework for large-scale data clustering. The main idea is to modify functional dimensionality reduction techniques to directly optimize over discrete labels using stochastic gradient descent...
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Chapter and Conference Paper
A Comparison of One-Class Classifiers for Novelty Detection in Forensic Case Data
This paper investigates the application of novelty detection techniques to the problem of drug profiling in forensic science. Numerous one-class classifiers are tried out, from the simple k-means to the more e...
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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...
