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Improved weight initialization for deep and narrow feedforward neural network
The problem of \textquotedblleft dying ReLU," where ReLU neurons become inactive and yield zero output, presents a significant challenge in the training of deep neural networks with ReLU activation function.
Algorithm Unrolling for Massive Access via Deep Neural Network with Theoretical Guarantee
Moreover, the proposed algorithm unrolling approach inherits the structure and domain knowledge of the ISTA, thereby maintaining the algorithm robustness, which can handle non-Gaussian preamble sequence matrix in massive access.
An algebraic-geometric approach for linear regression without correspondences
This naturally leads to a polynomial system of $n$ equations in $n$ unknowns, which contains $\xi^*$ in its root locus.
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