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Titlebook: Machine Learning and Knowledge Discovery in Databases; European Conference, Paolo Frasconi,Niels Landwehr,Jilles Vreeken Conference proceed

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Efficient Bayesian Maximum Margin Multiple Kernel Learning, local conjugacy for all other variables. Such geometry and conjugacy based posterior sampling leads to very fast mixing rate and scales linearly with the number of kernels used. Extensive experiments on classification tasks validate the superiority of the proposed method in both efficacy and efficiency.
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,Gaussian Process Pseudo-Likelihood Models for Sequence Labeling, capture multiple dependencies makes the proposed approach useful for a wide range of sequence labeling problems. Numerical experiments on some sequence labeling problems in natural language processing demonstrate the usefulness of the proposed approach.
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,Uncovering Locally Discriminative Structure for Feature Analysis,lso utilized to minimize distances between data from the same class. In addition, we use the kernel method to extend our proposed model and facilitate feature learning in a high-dimensional space after feature mapping. Experimental results show that our method is superior to all other compared methods over a number of datasets.
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,: Online Structure Learning Using Background Knowledge Axiomatization,cations, it is desirable to incrementally learn or revise the model’s structure and parameters. Experimental results are presented in activity recognition using a probabilistic variant of the Event Calculus (.) as background knowledge and a benchmark dataset for video surveillance.
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Bokai Cao,Chun-Ta Lu,Xiaokai Wei,Philip S. Yu,Alex D. Leowitigen Definition. Danach konkurrieren Aktivgeschäfte um die günstigste Refinanzierung durch Einlagen, umgekehrt konkurrieren diese Einlagen um eine Anlagemöglichkeit auf der Aktivseite. Dies läßt — so die Vertreter der Kapitalfondstheorie — eine Teilung der Zinsspanne zwischen Einlage und Anlage ni
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