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: The ideal candidate should have: * Knowledge of machine learning, especially neural networks or graph neural network or federated learning. * Strong mathematical and algorithmic background (optimization
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heterogeneous models can be combined within a unified framework to optimize trade-offs between accuracy, robustness, and computational cost. These contributions aim at advancing the understanding of adaptive
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efficient compression performance, each module relies on a rigid, manual design. Furthermore, these modules cannot be jointly optimized end-to-end. In parallel, recent years have seen the resounding success
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knowledge and requiring more robust selection strategies. - Generalize results to the "philosopher inequality" setting [4], where the benchmark is the optimal online algorithm rather than the expected maximum
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this new tool to improve knowledge regarding respiratory muscle structure and function within the Intensive Care Unit (ICU) with the ultimate goal to improve the management of these patients. Three different
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microfluidic chips (CAD Design). • Master microfabrication techniques: SLA 3D printing, PDMS molding, and cleanroom work. • Iterate on designs to optimize fluid circulation, mixing, and analyte incubation. B
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exhaustive), approximation schemes, series expansions, perturbation techniques, renormalization group methods, asymptotic analysis, optimization strategies, or coarse-grained/fine-grained approaches contribute