We give a polynomial time algorithm to decode multivariate polynomial codes of degree d up to half their minimum distance, when the evaluation points are an arbitrary product set S^m, for every d < |S|. Previously known algorithms could achieve this only if the set S has some very special algebraic structure, or if the degree d is significantly smaller than |S|. We also give a near-linear time algorithm, which is based on tools from list-decoding, to decode these codes from nearly half their minimum distance, provided d < (1-epsilon)|S| for constant epsilon > 0. Our result gives an m-dimensional generalization of the well known decoding algorithms for Reed-Solomon codes, and can be viewed as giving an algorithmic version of the Schwartz-Zippel lemma.
@InProceedings{kim_et_al:LIPIcs.CCC.2016.11, author = {Kim, John Y. and Kopparty, Swastik}, title = {{Decoding Reed-Muller Codes Over Product Sets}}, booktitle = {31st Conference on Computational Complexity (CCC 2016)}, pages = {11:1--11:28}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-008-8}, ISSN = {1868-8969}, year = {2016}, volume = {50}, editor = {Raz, Ran}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CCC.2016.11}, URN = {urn:nbn:de:0030-drops-58352}, doi = {10.4230/LIPIcs.CCC.2016.11}, annote = {Keywords: polynomial codes, Reed-Muller codes, coding theory, error-correcting codes} }
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