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Titlebook: Machine Learning and Knowledge Discovery in Databases; European Conference, Michele Berlingerio,Francesco Bonchi,Georgiana Ifr Conference p

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Scalable and Interpretable One-Class SVMs with Deep Learning and Random Fourier Features research as well as industrial applications. The biggest issue for OC-SVM is yet the capability to operate with large and high-dimensional datasets due to optimization complexity. Those problems might be mitigated via dimensionality reduction techniques such as manifold learning or autoencoder. How
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Pedestrian Trajectory Prediction with Structured Memory Hierarchiescoveries, we propose incorporating a structured memory component in the human trajectory prediction pipeline to capture historical information to improve performance. We introduce structured LSTM cells for modelling the memory content hierarchically, preserving the spatiotemporal structure of the in
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