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In this paper we develop a theory of matrix completion for the extreme case of noisy 1-bit observations.
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G. Miller · 1956
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D. Gabay and B. Mercier · 1976
Earlier work this paper cites.
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J. Barzilai and J. Borwein · 1988
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Earlier work this paper cites.
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A. Schein, L. Saul, and L. Ungar · 2003
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Earlier work this paper cites.
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