Automata, Languages, and Programming: 39th International by Dimitris Achlioptas, Ricardo Menchaca-Mendez (auth.), Artur PDF

By Dimitris Achlioptas, Ricardo Menchaca-Mendez (auth.), Artur Czumaj, Kurt Mehlhorn, Andrew Pitts, Roger Wattenhofer (eds.)

ISBN-10: 3642315933

ISBN-13: 9783642315930

ISBN-10: 3642315941

ISBN-13: 9783642315947

This two-volume set of LNCS 7391 and LNCS 7392 constitutes the refereed lawsuits of the thirty ninth foreign Colloquium on Automata, Languages and Programming, ICALP 2012, held in Warwick, united kingdom, in July 2012. the full of 123 revised complete papers awarded during this quantity have been conscientiously reviewed and chosen from 432 submissions. they're prepared in 3 tracks focussing on algorithms, complexity and video games; common sense, semantics, automata and idea of programming; and foundations of networked computation.

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Additional info for Automata, Languages, and Programming: 39th International Colloquium, ICALP 2012, Warwick, UK, July 9-13, 2012, Proceedings, Part I

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We obtain our protocols in the non-simultaneous model by extending the ideas of Grolmusz [10] and Pudl´ak [17]. We combine this with a beautiful lemma of Babai et al. 10] in order to make our protocols simultaneous: Lemma 2 ([2]). Suppose k > 1 + logn and let X be a k × n boolean matrix given as an input for a k-party communication problem. Let ni be the number of columns of X with Hamming weight i. Then by communicating O(k2 log n) bits, the players can compute ni for all i in the simultaneous deterministic model.

Yn ) = −1 iff ∑nj=1 y j = 0 mod m. In this section we show that the complexity of MODm ◦ g is determined by the quantity |S0 | − |S1 | , where Si is the subset of the support of g that consists of all inputs whose Hamming weight has parity i. Part (b) of Theorem 2 is important because it will be used to derive the lower bound in the next subsection. Theorem 2. Let m ≥ 2 be an integer. The function MODm ◦ g satisfies: || (a) If m divides |S0 | − |S1|, then Dk (MODm ◦ g) ≤ k log m . (b) Otherwise, Rεk (MOD m ◦ g) ≥ m5n 2 4k + log(1 − 2ε) − (k + 1) logm − 1.

Finally, we note that ⎞ ⎛ ⎛ ⎞ ∞ E [min{l0 , l1 }] = i=0 i ⎝2Poi(λ, i) ⎝1 − i−1 2 Poi(λ, j)⎠ − (Poi(λ, i)) ⎠ . (11) j=0 To compute a rigorous lower bound for (11) one now simply truncates the sum at any desired level of accuracy. 12 D. Achlioptas and R. Menchaca-Mendez Acknowledgements. We are grateful to Andrea Montanari for a number of useful conversations. References 1. : Optimal myopic algorithms for random 3-sat. In: Proceedings of the 41st Annual Symposium on Foundations of Computer Science 2000, pp.

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Automata, Languages, and Programming: 39th International Colloquium, ICALP 2012, Warwick, UK, July 9-13, 2012, Proceedings, Part I by Dimitris Achlioptas, Ricardo Menchaca-Mendez (auth.), Artur Czumaj, Kurt Mehlhorn, Andrew Pitts, Roger Wattenhofer (eds.)


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