TY - GEN
T1 - Local Decoding and Update of Compressed Data
AU - Vatedka, Shashank
AU - Tchamkerten, Aslan
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7/1
Y1 - 2019/7/1
N2 - In compressing large datasets it is often desirable to guarantee locality properties that allow the efficient decoding and efficient update of short fragments of data. This paper proposes a universal compression scheme for memoryless sources with the following features: 1. the rate can be made arbitrarily close to the entropy of the underlying source, 2. constant-sized (as a function of the blocklength) fragments of the source can be recovered by probing a constant number of codeword bits on average, 3. the update of constant-sized fragments of the source can be achieved by reading and modifying a constant number of codeword symbols on average, and 4. the overall encoding and decoding complexity is quasilinear in the blocklength of the source.
AB - In compressing large datasets it is often desirable to guarantee locality properties that allow the efficient decoding and efficient update of short fragments of data. This paper proposes a universal compression scheme for memoryless sources with the following features: 1. the rate can be made arbitrarily close to the entropy of the underlying source, 2. constant-sized (as a function of the blocklength) fragments of the source can be recovered by probing a constant number of codeword bits on average, 3. the update of constant-sized fragments of the source can be achieved by reading and modifying a constant number of codeword symbols on average, and 4. the overall encoding and decoding complexity is quasilinear in the blocklength of the source.
UR - https://www.scopus.com/pages/publications/85073166363
U2 - 10.1109/ISIT.2019.8849634
DO - 10.1109/ISIT.2019.8849634
M3 - Conference contribution
AN - SCOPUS:85073166363
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 572
EP - 576
BT - 2019 IEEE International Symposium on Information Theory, ISIT 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE International Symposium on Information Theory, ISIT 2019
Y2 - 7 July 2019 through 12 July 2019
ER -