DocumentCode
1708761
Title
Information Cost Tradeoffs for Augmented Index and Streaming Language Recognition
Author
Chakrabarti, Amit ; Cormode, Graham ; Kondapally, Ranganath ; McGregor, Andrew
Author_Institution
Dartmouth Coll., Staten Island, NH, USA
fYear
2010
Firstpage
387
Lastpage
396
Abstract
This paper makes three main contributions to the theory of communication complexity and stream computation. First, we present new bounds on the information complexity of AUGMENTED-INDEX. In contrast to analogous results for INDEX by Jain, Radhakrishnan and Sen [J. ACM, 2009], we have to overcome the significant technical challenge that protocols for AUGMENTED-INDEX may violate the "rectangle property" due to the inherent input sharing. Second, we use these bounds to resolve an open problem of Magniez, Mathieu and Nayak [STOC, 2010] on the multi-pass complexity of recognizing Dyck languages. This results in a natural separation between the standard multi-pass model and the multi-pass model that permits reverse passes. Third, we present the first passive memory checkers that verify the interaction transcripts of priority queues, stacks, and double-ended queues. We obtain tight upper and lower bounds for these problems, thereby addressing an important sub-class of the memory checking framework of Blum et al. [Algorithmica, 1994].
Keywords
computational complexity; computational linguistics; Dyck language recognition; augmented index; communication complexity; information cost tradeoffs; passive memory checkers; rectangle property; streaming language recognition; Artificial intelligence; Complexity theory; Educational institutions; Entropy; Indexes; Mutual information; Protocols; augmented index; communication complexity; data streams; lower bounds; memory checking;
fLanguage
English
Publisher
ieee
Conference_Titel
Foundations of Computer Science (FOCS), 2010 51st Annual IEEE Symposium on
Conference_Location
Las Vegas, NV
ISSN
0272-5428
Print_ISBN
978-1-4244-8525-3
Type
conf
DOI
10.1109/FOCS.2010.44
Filename
5671220
Link To Document