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Oral
Weak Detection of Signal in the Spiked Wigner Model
Hye Won Chung · Ji Oon Lee

Tue Jun 11 05:00 PM -- 05:05 PM (PDT) @ Room 103
in Statistical Learning Theory »

We consider the problem of detecting the presence of the signal in a rank-one signal-plus-noise data matrix. In case the signal-to-noise ratio is under the threshold below which a reliable detection is impossible, we propose a hypothesis test based on the linear spectral statistics of the data matrix. The error of the proposed test is optimal as it matches the error of the likelihood ratio test that minimizes the sum of the Type-I and Type-II errors. The test is data-driven and does not depend on the distribution of the signal or the noise. If the density of the noise is known, it can be further improved by an entrywise transformation to lower the error of the test.

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Author Information

Hye Won Chung (KAIST)
Ji Oon Lee (KAIST)

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