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Devoted to multi-task learning and structured output learning, operator-valued kernels provide a flexible tool to build vector-valued functions in the context of Reproducing Kernel Hilbert Spaces. To scale up these methods, we extend the celebrated Random Fourier Feature methodology to get an approximation of operator-valued kernels. We propose a general(More)
OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. Abstract The complex mechanical behaviour of composite materials, due to internal heterogeneity and multi-layered composition impose deeper studies. This paper presents an experimental investigation technique to(More)
Random Forests (RFs) are strong machine learning tools for classification and regression. However, they remain supervised algorithms, and no extension of RFs to the one-class setting has been proposed, except for techniques based on second-class sampling. This work fills this gap by proposing a natural methodology to extend standard splitting criteria to(More)
Global behaviour of a composite stiffened panel in buckling. Part 2: Experimental investigation. OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. a b s t r a c t The present study analyses an aircraft composite fuselage structure manufactured by the Liquid Resin(More)
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