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investigate and develop adaptive techniques for selecting hyperparameters, in order to reduce the tuning effort. For instance, the stochastic Polyak step size and its recent variants have shown promising
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industrial groups, competitiveness clusters, research and higher education players, laboratories of excellence, technological research institute, etc. Contexte et atouts du poste The project lies
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pathology (morphology) and spatial transcriptomics. Test, change up until validation the XAI solutions Design experimental platform of virtual spatial transcriptomics Develop programs/applications/interfaces
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. Supervised learning is one of the main branches in Artificial Intelligence (AI). Training a model requires an ensemble of data to train on. Each data item is associated with a label, which is the best
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complexity and large number of parameters. Tensors are a natural way to represent high dimensional data for numerous applications in computational science and data science [1]. CP, Tucker and Tensor Train are
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return to a normal life through innovative remote monitoring solutions. One of the objectives of the I-DEAL project is to develop a home-based system for early detection of CD flares, that enable timely
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complexity in practice might provide fewer benefits as it could be expected from analytical derivations. The reason is the overhead caused by specific hardware we use to train or execute neural networks
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. The reason is the overhead caused by specific hardware we use to train or execute neural networks. To make deep learning algorithms efficient in real life it is important to combine software and hardware
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industrial groups, competitiveness clusters, research and higher education players, laboratories of excellence, technological research institute, etc. Contexte et atouts du poste Context and background
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investigate several facets of the algorithms and the design processes, and ultimately provide this application to the broad scientific community. The main goal of the PhD project is to develop a deep generative