I have always been feeling somewhat awkward that my most cited paper has been an industrial pre-machine-learning paper on how to extract geographic references from a text.

Recently, our 2009 paper in American Mathematical Monthly on non-zero self-distances has finally surpassed it in the number of citations.

Meanwhile, my two papers I like the most have exactly zero citations.

5 months in a new job: among software achievements: now I know how to take autocomputed gradients with respect to variables assembled inside nested dictionaries. So I am no longer forced to reshape complicated tree-like-structures into flat arrays in order to use differentiable programming.

As a result, I can finally experiment with DMM training using gradient methods without putting too much labor into those experiments.

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