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A No-Go Theorem for Derandomized Parallel Repetition: Beyond Feige-Kilian.

, , и . APPROX-RANDOM, том 60 из LIPIcs, стр. 42:3-42:29. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2016)

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Antonios K Danassis

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Другие публикации лиц с тем же именем

Improved Approximation Algorithms for Projection Games - (Extended Abstract)., и . ESA, том 8125 из Lecture Notes in Computer Science, стр. 683-694. Springer, (2013)NP-hardness of approximately solving linear equations over reals., и . STOC, стр. 413-420. ACM, (2011)Regularization of Low Error PCPs and an Application to MCSP., и . ISAAC, том 283 из LIPIcs, стр. 39:1-39:16. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2023)Mixing Implies Lower Bounds for Space Bounded Learning., и . COLT, том 65 из Proceedings of Machine Learning Research, стр. 1516-1566. PMLR, (2017)Nearly Optimal Pseudorandomness From Hardness., , , и . FOCS, стр. 1057-1068. IEEE, (2020)Sub-constant error low degree test of almost-linear size., и . STOC, стр. 21-30. ACM, (2006)Amplification and Derandomization without Slowdown., и . FOCS, стр. 770-779. IEEE Computer Society, (2016)Tighter MA/1 Circuit Lower Bounds from Verifier Efficient PCPs for PSPACE., и . APPROX/RANDOM, том 275 из LIPIcs, стр. 55:1-55:22. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2023)Reduction from Non-Unique Games to Boolean Unique Games., и . ITCS, том 215 из LIPIcs, стр. 64:1-64:25. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2022)Entropy Samplers and Strong Generic Lower Bounds For Space Bounded Learning., и . ITCS, том 94 из LIPIcs, стр. 28:1-28:20. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2018)