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Beyond IID weights: sparse and low-rank deep Neural Networks are also Gaussian Processes
The infinitely wide neural network has been proven a useful and manageable mathematical model that enables the understanding of many phenomena appearing in deep learning.
Beyond Independent Measurements: General Compressed Sensing with GNN Application
When the structure is given as a possibly non-convex cone $T \subset \mathbb{R}^{n}$, an approximate empirical risk minimizer is proven to be a robust estimator if the effective number of measurements is sufficient, even in the presence of a model mismatch.
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