Doubly robust nearest neighbors in factor models. (arXiv:2211.14297v3 [stat.ML] UPDATED)

We introduce and analyze an improved variant of nearest neighbors (NN) for
estimation with missing data in latent factor models. We consider a matrix
completion problem with missing data, where the $(i, t)$-th entry, when
observed, is given by its mean $f(u_i, v_t)$ plus mean-zero noise for an
unknown function $f$ and latent factors $u_i$ and $v_t$. Prior NN strategies,
like unit-unit NN, for estimating the mean $f(u_i, v_t)$ relies on existence of
other rows $j$ with $u_j \approx u_i$. …

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