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Outlier Detection Using Generative Models with Theoretical Performance Guarantees
We propose an outlier detection approach for reconstructing the ground-truth signals modeled by generative models under sparse outliers.
Optimal Compression for Minimizing Classification Error Probability: an Information-Theoretic Approach
We then provide analytical and computational methods to characterize the optimal trade-off between data compression and classification error probability.
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