Any low-success-probability LPN solver can be transformed into a high-success-probability solver on scaled parameters LPN with noise and dimension divided by k = Θ(1/δ log 1/ε).
Proceedings of the Thirty-Seventh Annual ACM Symposium on Theory of Computing , pages =
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A review describing the Decoded Quantum Interferometry algorithm for quantum speedups in max-LINSAT optimization, with claimed superpolynomial advantage in the OPI problem.
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Hardness Amplification for (Sparse) LPN
Any low-success-probability LPN solver can be transformed into a high-success-probability solver on scaled parameters LPN with noise and dimension divided by k = Θ(1/δ log 1/ε).
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Quantum Decoding Algorithms: Quantum Speedups in Optimization
A review describing the Decoded Quantum Interferometry algorithm for quantum speedups in max-LINSAT optimization, with claimed superpolynomial advantage in the OPI problem.