{{sda:pics:sda2-small.png?135}} {{sda:pub:skip.png?45}} {{sda:pics:SFdS.jpg?101}} {{sda:pics:SFC.jpg?75}} {{sda:pics:EGC.jpg?88}} {{sda:pics:LC-UPD.jpg?166}} {{sda:pub:s5_logo.png?90}} ====== Slides ====== * Vladimir Batagelj, Daria Maltseva: {{sda:pub:p19-batagelj.pdf|Temporal bibliographic analysis}} * Christophe Biernacki: {{sda:pub:p19_biernacki1.pdf|MASSICCC: A SaaS Platform for Clustering and Co-Clustering of Mixed Data}}. * Christophe Biernacki, M. Marbac-Lourdelle, V. Vandewalle: {{sda:pub:p19_biernacki2.pdf|Gaussian Based Visualization of Gaussian and Non-Gaussian Based Clustering}}. * Paula Brito: {{sda:pub:p19_brito.pdf|Symbolic Data Analysis: Past, Present and Future}}. * Dominique Desbois: {{sda:pub:p19_desbois.pdf|Exploring the distribution of conditional quantile estimate ranges}}. * Edwin Diday: {{sda:pub:p19_diday.docx|Explanatory tools for Machine Learning in the Symbolic Data Analysis Framework}}. * Edwin Diday: {{sda:pub:p19_diday.pptx|Concordance and discordance of classes in the SDA framework}}. * Richard Emilion: {{sda:pub:p19_emilion.pdf|Likelihood in the symbolic context. Examples}}. * Yves Lechevallier, Francisco de A. T. de Carvalho: {{sda:pub:p19_lechevallier.pdf|Weighted Multi-view Partitioning of Time Series}}. * Andrej Srakar: {{sda:pub:p19_srakar.pdf|Symbolic input output analysis: harmonic analysis approach to combine statistical distributions}}. \\ \\ [[sda:meet:pa19|Back to Paris'19]]