Brice Platerrier

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Programmable stochastic self-assembly of modular robots provides promising means to formation of structures at different scales. Formalisms based on graph grammars and rule-based approaches have been previously published for controlling the self-assembly process. While several rule-synthesis algorithms have been proposed, formal synthesis of rulesets has(More)
During this week’s practical we will cover two more manifold learning algorithms, namely (i) Laplacian Eigenmaps and (ii) Isomaps, and compare their projections to kernel PCA. We will then perform Spectral Clustering, which involves applying K-means on the projections of these non-linear embeddings. Finally, we will evaluate the kernel K-Means algorithm,(More)
During this week’s practical we will cover two more manifold learning algorithms, namely (i) Laplacian Eigenmaps and (ii) Isomaps, and compare their projections to kernel PCA. We will then perform Spectral Clustering, which involves applying K-means on the projections of these non-linear embeddings. Finally, we will evaluate the kernel K-Means algorithm,(More)
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