Titlebook: Machine Learning, Optimization, and Data Science; 4th International Co Giuseppe Nicosia,Panos Pardalos,Vincenzo Sciacca Conference proceedi

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978-3-030-13708-3Springer Nature Switzerland AG 2019

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Machine Learning, Optimization, and Data Science978-3-030-13709-0Series ISSN 0302-9743 Series E-ISSN 1611-3349

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https://doi.org/10.1007/978-3-030-13709-0deep learning; machine learning; reinforcement learning; neural networks; deep reinforcement learning; op

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Classification and Survival Prediction in Diffuse Large B-Cell Lymphoma by Gene Expression Profilinelies on several already known classification methods. We make use of the model for a survival analysis of tumor and immune subtype from Diffuse Large B-cell Lymphoma patients. Experimental analyses show good level of accuracy in the detection of Cell-of-Origin of diseases.

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Average Performance Analysis of the Stochastic Gradient Method for Online PCA,nline approach for selecting the learning rate. Simulation experiments confirm the practical relevance of the plain stochastic gradient approach and that drastic improvements can be achieved by learning the learning rate.

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Introduction,preted, before setting the notional framework within which the media in general and images in particular will be studied—how they (literally) mediate between the real and the receiver: in other words, how they enable but also shape the audience’s interpretation of reality. Finally, it describes the