Titlebook: Data Science, Learning by Latent Structures, and Knowledge Discovery; Berthold Lausen,Sabine Krolak-Schwerdt,Matthias Bö Conference procee

cardiac-arrest

Recent Progress in Complex Network Analysis: Models of Random Intersection Graphs common neighbor. This tendency in theoretical random graph models is depicted by the asymptotically constant clustering coefficient. Moreover complex networks have power law degree distribution and small diameter (small world phenomena), thus these are desirable features of random graphs used for m

Immunization

jaunty

Heresy

Isometric

希望

On-Line Clustering of Functional Boxplots for Monitoring Multiple Streaming Time Serieserlapping windows. It is a two-step strategy which performs at first, an on-line summarization by means of functional data structures, named Functional Boxplot micro-clusters; then, it reveals the final summarization by processing, off-line, the functional data structures. Our main contribute consis

ANT

不妥协

P2P RVM for Distributed Classificationetworks and support applications. Mining patterns in such distributed and dynamic environment is a challenging task, because centralization of data is not feasible. In this paper, we have proposed a distributed classification technique based on relevance vector machines (RVM) and local model exchang

onlooker

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