On Blackbox Backpropagation and Jacobian Sensing

NeurIPS 2017 Krzysztof M. ChoromanskiVikas Sindhwani

From a small number of calls to a given “blackbox" on random input perturbations, we show how to efficiently recover its unknown Jacobian, or estimate the left action of its Jacobian on a given vector. Our methods are based on a novel combination of compressed sensing and graph coloring techniques, and provably exploit structural prior knowledge about the Jacobian such as sparsity and symmetry while being noise robust... (read more)

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