High-dimensional regression with noisy and missing data: Provable guarantees with non-convexity

Although the standard formulations of prediction problems involve fully-observed and noiseless data drawn in an i.i.d. manner, many applications involve noisy and/or missing data, possibly involving dependencies... (read more)

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