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Information and Computation
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Foundations and Trends® in Theoretical Computer Science
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Theoretical Computer Science
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FOCS '08 Proceedings of the 2008 49th Annual IEEE Symposium on Foundations of Computer Science
Polylog Space Compression Is Incomparable with Lempel-Ziv and Pushdown Compression
SOFSEM '09 Proceedings of the 35th Conference on Current Trends in Theory and Practice of Computer Science
Lower bounds for processing data with few random accesses to external memory
Journal of the ACM (JACM)
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CPM '09 Proceedings of the 20th Annual Symposium on Combinatorial Pattern Matching
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MFCS '09 Proceedings of the 34th International Symposium on Mathematical Foundations of Computer Science 2009
LZ77-Like Compression with Fast Random Access
DCC '10 Proceedings of the 2010 Data Compression Conference
Lightweight data indexing and compression in external memory
LATIN'10 Proceedings of the 9th Latin American conference on Theoretical Informatics
Grammar-based codes: a new class of universal lossless source codes
IEEE Transactions on Information Theory
Universal lossless compression via multilevel pattern matching
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
MFCS'07 Proceedings of the 32nd international conference on Mathematical Foundations of Computer Science
Processing compressed texts: a tractability border
CPM'07 Proceedings of the 18th annual conference on Combinatorial Pattern Matching
Faster approximate pattern matching in compressed repetitive texts
ISAAC'11 Proceedings of the 22nd international conference on Algorithms and Computation
On the value of multiple read/write streams for data compression
Information Theory, Combinatorics, and Search Theory
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We show that, given a string s of length n, with constant memory and logarithmic passes over a constant number of streams we can build a context-free grammar that generates s and only s and whose size is within an ${\mathcal O}\left({\min \left( g \log g, \sqrt{n / \log n} \right)}\right)$-factor of the minimum g. This stands in contrast to our previous result that, with polylogarithmic memory and polylogarithmic passes over a single stream, we cannot build such a grammar whose size is within any polynomial of g.