Title
Local List Recovery of High-Rate Tensor Codes & Applications
Abstract
In this work, we give the first construction of high-rate locally list-recoverable codes. List-recovery has been an extremely useful building block in coding theory, and our motivation is to use these codes as such a building block. In particular, our construction gives the first capacity-achieving locally list-decodable codes (over constant-sized alphabet); the first capacity achieving globally list-decodable codes with nearly linear time list decoding algorithm (once more, over constant-sized alphabet); and a randomized construction of binary codes on the Gilbert-Varshamov bound that can be uniquely decoded in near-linear-time, with higher rate than was previously known. Our techniques are actually quite simple, and are inspired by an approach of Gopalan, Guruswami, and Raghavendra (Siam Journal on Computing, 2011) for list-decoding tensor codes. We show that tensor powers of (globally) list-recoverable codes are `approximately' locally list-recoverable, and that the `approximately' modifier may be removed by pre-encoding the message with a suitable locally decodable code. Instantiating this with known constructions of high-rate globally list-recoverable codes and high-rate locally decodable codes finishes the construction.
Year
DOI
Venue
2017
10.1109/FOCS.2017.27
2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS)
Keywords
DocType
Volume
error correcting codes,coding theory,tensor codes,list recovery,local list recovery
Conference
24
ISSN
ISBN
Citations 
0272-5428
978-1-5386-3465-3
5
PageRank 
References 
Authors
0.41
24
3
Name
Order
Citations
PageRank
Brett Hemenway1141.01
Noga Ron-Zewi2409.89
Mary Wootters317225.99