Unbiased bits from sources of weak randomness and probabilistic communication complexity
SIAM Journal on Computing - Special issue on cryptography
Private vs. common random bits in communication complexity
Information Processing Letters
String matching under a general matching relation
Information and Computation
Communication complexity
Journal of Algorithms
Maintaining Stream Statistics over Sliding Windows
SIAM Journal on Computing
Some complexity questions related to distributive computing(Preliminary Report)
STOC '79 Proceedings of the eleventh annual ACM symposium on Theory of computing
Approximating Edit Distance Efficiently
FOCS '04 Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science
The communication complexity of the Hamming distance problem
Information Processing Letters
Faster pattern matching with character classes using prime number encoding
Journal of Computer and System Sciences
Exact and Approximate Pattern Matching in the Streaming Model
FOCS '09 Proceedings of the 2009 50th Annual IEEE Symposium on Foundations of Computer Science
Pattern matching in multiple streams
CPM'12 Proceedings of the 23rd Annual conference on Combinatorial Pattern Matching
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We present space lower bounds for online pattern matching under a number of different distance measures. Given a pattern of length m and a text that arrives one character at a time, the online pattern matching problem is to report the distance between the pattern and a sliding window of the text as soon as the new character arrives. We require that the correct answer is given at each position with constant probability. We give Ω(m) bit space lower bounds for L1, L2, L∞, Hamming, edit and swap distances as well as for any algorithm that computes the cross-correlation/convolution. We then show a dichotomy between distance functions that have wildcard-like properties and those that do not. In the former case which includes, as an example, pattern matching with character classes, we give Ω(m) bit space lower bounds. For other distance functions, we show that there exist space bounds of Ω(log m) and O(log2 m) bits. Finally we discuss space lower bounds for non-binary inputs and show how in some cases they can be improved.