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quant-ph2026
On the coherent extension of some Fano-type learning bounds
Evan Peters
Information theory provides tools to predict the performance of a learning algorithm on a given dataset. For instance, the accuracy of learning an unknown parameter can be upper bo…
quant-ph2025
Importance sampling for data-driven decoding of quantum error-correcting codes
Evan Peters
Data-driven decoding (DDD) - learning to decode syndromes of (quantum) error-correcting codes by learning from data - can be a difficult problem due to several atypical and poorly…