@inproceedings{91fda706134e4b12bc032b56d7bcdd82,
title = "Robust local testability of tensor products of LDPC codes",
abstract = "Given two binary linear codes R and C, their tensor product R ⊗ C consists of all matrices with rows in R and columns in C. We analyze the {"}robustness{"} of the following test for this code (suggested by Ben-Sasson and Sudan [6]): Pick a random row (or column) and check if the received word is in R (or C). Robustness of the test implies that if a matrix M is far from R ⊗ C, then a significant fraction of the rows (or columns) of M are far from codewords of R (or C). We show that this test is robust, provided one of the codes is what we refer to as smooth. We show that expander codes and locally-testable codes are smooth. This complements recent examples of P. Valiant [13] and Coppersmith and Rudra [9] of codes whose tensor product is not robustly testable.",
author = "Irit Dinur and Madhu Sudan and Avi Wigderson",
year = "2006",
doi = "10.1007/11830924_29",
language = "אנגלית",
isbn = "3540380442",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "304--315",
booktitle = "Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques - 9th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2006 a",
address = "גרמניה",
note = "9th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2006 and 10th International Workshop on Randomization and Computation, RANDOM 2006 ; Conference date: 28-08-2006 Through 30-08-2006",
}