Empirical comparison finds supervised training yields higher accuracy on convex l1 problems while unsupervised training provides better robustness to distribution shift on nonconvex l0 problems for deep-unfolded ISTA and IHT.
Trainable projected gradient detector for massive overloaded MIMO channels: Data-driven tuning approach
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Comparison between Supervised and Unsupervised Learning in Deep Unfolded Sparse Signal Recovery
Empirical comparison finds supervised training yields higher accuracy on convex l1 problems while unsupervised training provides better robustness to distribution shift on nonconvex l0 problems for deep-unfolded ISTA and IHT.