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Titlebook: Computing and Combinatorics; 16th Annual Internat My T. Thai,Sartaj Sahni Conference proceedings 2010 Springer-Verlag Berlin Heidelberg 201

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發(fā)表于 2025-3-21 19:17:59 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Computing and Combinatorics
副標(biāo)題16th Annual Internat
編輯My T. Thai,Sartaj Sahni
視頻videohttp://file.papertrans.cn/235/234767/234767.mp4
概述Up-to-date results.Fast track conference proceedings.State-of-the-art report
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Computing and Combinatorics; 16th Annual Internat My T. Thai,Sartaj Sahni Conference proceedings 2010 Springer-Verlag Berlin Heidelberg 201
出版日期Conference proceedings 2010
關(guān)鍵詞Editing; Extension; Kernel; Permutation; automata; combinatorics; complexity; computational geometry; crypto
版次1
doihttps://doi.org/10.1007/978-3-642-14031-0
isbn_softcover978-3-642-14030-3
isbn_ebook978-3-642-14031-0Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2010
The information of publication is updating

書目名稱Computing and Combinatorics影響因子(影響力)




書目名稱Computing and Combinatorics影響因子(影響力)學(xué)科排名




書目名稱Computing and Combinatorics網(wǎng)絡(luò)公開度




書目名稱Computing and Combinatorics網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Computing and Combinatorics被引頻次




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書目名稱Computing and Combinatorics讀者反饋學(xué)科排名




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Boxicity and Poset Dimension,..]×[..,..]×???×[..,..]. The . of ., box(.) is the minimum integer . such that . can be represented as the intersection graph of .-dimensional boxes, i.e. each vertex is mapped to a .-dimensional box and two vertices are adjacent in . if and only if their corresponding boxes intersect. Let . be a p
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On the Hardness against Constant-Depth Linear-Size Circuitsation, as there are general derandomization results which are based on the assumption that average-case hard functions exist. However, to achieve a complete derandomization, one usually needs a function which is extremely hard against a complexity class, in the sense that any algorithm in the class
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The Curse of Connectivity: ,-Total Vertex (Edge) Coverly .-. and .-.. Specifically, we impose the additional requirement that each connected component of a solution have at least . vertices (resp. edges from the solution), and call the problem .-. (resp. .-.). We show that
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Clustering with or without the Approximationollow-up papers. The input for the clustering problem consists of points in a metric space and a number ., specifying the desired number of clusters. The algorithms find a clustering that is provably close to a target clustering, provided that the instance has the “( 1?+?., .)-property”, which means
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