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We give a tight characterization of the (vectorized Euclidean) norm of weights required to realize a function f : R^d -> R as a single hidden-layer ReLU network with an unbounded number of units (infinite width), extending the univariate characterization of Savarese et al. (2019) to the multivariate case.  more » « less
Award ID(s):
1740707 1934637
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
International Conference on Learning Representations
Medium: X
Sponsoring Org:
National Science Foundation
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