Proposes an adaptive hybrid estimator for common mean estimation under independent but non-identical symmetric unimodal distributions, with near-optimality guarantees even when only log n / n samples are low-noise.
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Estimating location parameters in entangled single-sample distributions
Proposes an adaptive hybrid estimator for common mean estimation under independent but non-identical symmetric unimodal distributions, with near-optimality guarantees even when only log n / n samples are low-noise.