January 2004
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Advances in Neural Information Processing Systems
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... Matrix completion aims to predict the unknown entries of a partially observed matrix using its known elements by minimizing a criterion such as the mean squared error, typically subject to a low-rank constraint. While early work on matrix completion dates back to, among others, Achlioptas & McSherry (2001), Srebro et al. (2004), and Rennie & Srebro (2005), it has been actively studied since Candès & Recht (2009) and Candès & Tao (2010). For overviews, we refer to, e.g., Mazumder et al. (2010), Hastie et al. (2015), Davenport & Romberg (2016), Fithian & Mazumder (2018), and Nguyen et al. (2019). ...
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January 2004
Advances in Neural Information Processing Systems