Workshop on Analytic Algorithmics and Combinatorics最新文献_第9页

The Spanning Trees Formulas in a Class of Double Fixed-Step Loop Networks 一类双固定步长环网的生成树公式

Workshop on Analytic Algorithmics and Combinatorics Pub Date : 2009-01-03 DOI: 10.1137/1.9781611972993.3

T. Atajan, N. Otsuka, Xuerong Yong

引用次数: 1

Mathematics and Computer Science Serving/Impacting Bioinformatics 服务/影响生物信息学的数学和计算机科学

Workshop on Analytic Algorithmics and Combinatorics Pub Date : 2009-01-03 DOI: 10.1137/1.9781611972993.5

G. Gonnet

引用次数: 0

Maximum Likelihood Analysis of Heapsort 堆排序的最大似然分析

Workshop on Analytic Algorithmics and Combinatorics Pub Date : 2009-01-03 DOI: 10.1137/1.9781611972993.7

Ulrich Laube, M. Nebel

引用次数: 0

Average-case Analysis of Moves in Quick Select 快速选择招式的平均案例分析

Workshop on Analytic Algorithmics and Combinatorics Pub Date : 2009-01-03 DOI: 10.1137/1.9781611972993.6

H. Mahmoud

引用次数: 5

Balanced And/Or Trees and Linear Threshold Functions 平衡和/或树和线性阈值函数

Workshop on Analytic Algorithmics and Combinatorics Pub Date : 2009-01-03 DOI: 10.1137/1.9781611972993.8

Hervé Fournier, Danièle Gardy, Antoine Genitrini

引用次数: 9

Pursuit and Evasion from a Distance: Algorithms and Bounds 远距离追逐与逃避:算法与界限

Workshop on Analytic Algorithmics and Combinatorics Pub Date : 2009-01-03 DOI: 10.1137/1.9781611972993.1

A. Bonato, E. Chiniforooshan

引用次数: 19

Approximating L1-distances Between Mixture Distributions Using Random Projections 用随机投影近似混合分布之间的l1距离

Workshop on Analytic Algorithmics and Combinatorics Pub Date : 2008-04-07 DOI: 10.1137/1.9781611972993.11

Satyaki Mahalanabis, Daniel Stefankovic

引用次数: 3

Markovian Embeddings of General Random Strings 一般随机字符串的马尔可夫嵌入

Workshop on Analytic Algorithmics and Combinatorics Pub Date : 2008-01-19 DOI: 10.1137/1.9781611972986.2

M. Lladser

{"title":"Markovian Embeddings of General Random Strings","authors":"M. Lladser","doi":"10.1137/1.9781611972986.2","DOIUrl":"https://doi.org/10.1137/1.9781611972986.2","url":null,"abstract":"Let A be a finite set and X a sequence of A-valued random variables. We do not assume any particular correlation structure between these random variables; in particular, X may be a non-Markovian sequence. An adapted embedding of X is a sequence of the form R(X1), R(X1,X2), R(X1,X2,X3), etc where R is a transformation defined over finite length sequences. In this extended abstract we characterize a wide class of adapted embeddings of X that result in a first-order homogeneous Markov chain. We show that any transformation R has a unique coarsest refinement R' in this class such that R'(X1), R'(X1,X2), R'(X1,X2,X3), etc is Markovian. (By refinement we mean that R'(u) = R'(v) implies R(u) = R(v), and by coarsest refinement we mean that R' is a deterministic function of any other refinement of R in our class of transformations.) We propose a specific embedding that we denote as RX which is particularly amenable for analyzing the occurrence of patterns described by regular expressions in X. A toy example of a non-Markovian sequence of 0's and 1's is analyzed thoroughly: discrete asymptotic distributions are established for the number of occurrences of a certain regular pattern in X1, ..., Xn as n → ∞ whereas a Gaussian asymptotic distribution is shown to apply for another regular pattern.","PeriodicalId":340112,"journal":{"name":"Workshop on Analytic Algorithmics and Combinatorics","volume":"245 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129070829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

On the Convergence of Upper Bound Techniques for the Average Length of Longest Common Subsequences 关于最长公共子序列平均长度上界技术的收敛性

Workshop on Analytic Algorithmics and Combinatorics Pub Date : 2008-01-19 DOI: 10.1137/1.9781611972986.1

G. S. Lueker

{"title":"On the Convergence of Upper Bound Techniques for the Average Length of Longest Common Subsequences","authors":"G. S. Lueker","doi":"10.1137/1.9781611972986.1","DOIUrl":"https://doi.org/10.1137/1.9781611972986.1","url":null,"abstract":"It has long been known [2] that the average length of the longest common subsequence of two random strings of length n over an alphabet of size k is asymptotic to γkn for some constant γk depending on k. The value of these constants remains unknown, and a number of papers have proved upper and lower bounds on them. In particular, in [6] we used a modification of methods of [3, 4] for determining lower and upper bounds on γk, combined with large computer computations, to obtain improved bounds on γ2. The method of [6] involved a parameter h; empirically, increasing h increased the computation time but gave better upper bounds. Here we show, for arbitrary k, a sufficient condition for a parameterized method to produce a sequence of upper bounds approaching the true value of γk, and show that a generalization of the method of [6] meets this condition for all k ≥ 2. While [3, 4] do not explicitly discuss how to parameterize their method, which is based on a concept they call domination, to trade off the tightness of the bound vs. the amount of computation, we discuss a very natural parameterization of their method; for the case of alphabet size k = 2 we conjecture but do not prove that it also meets the sufficient condition and hence also yields a sequence of bounds that converges to the correct value of γ2. For k > 2, it does not meet our sufficient condition. Thus we leave open the question of whether some method based on the undominated collations of [3, 4] gives bounds converging to the correct value for any k ≥ 2.","PeriodicalId":340112,"journal":{"name":"Workshop on Analytic Algorithmics and Combinatorics","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129400143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Nearly Tight Bounds on the Encoding Length of the Burrows-Wheeler Transform Burrows-Wheeler变换编码长度的近紧界

Workshop on Analytic Algorithmics and Combinatorics Pub Date : 2008-01-19 DOI: 10.1137/1.9781611972986.3

Ankur Gupta, R. Grossi, J. Vitter

{"title":"Nearly Tight Bounds on the Encoding Length of the Burrows-Wheeler Transform","authors":"Ankur Gupta, R. Grossi, J. Vitter","doi":"10.1137/1.9781611972986.3","DOIUrl":"https://doi.org/10.1137/1.9781611972986.3","url":null,"abstract":"In this paper, we present a nearly tight analysis of the encoding length of the Burrows-Wheeler Transform (BWT) that is motivated by the text indexing setting. For a text T of n symbols drawn from an alphabet Σ, our encoding scheme achieves bounds in terms of the hth-order empirical entropy Hh of the text, and takes linear time for encoding and decoding. We also describe a lower bound on the encoding length of the BWT that constructs an infinite (non-trivial) class of texts that are among the hardest to compress using the BWT. We then show that our upper bound encoding length is nearly tight with this lower bound for the class of texts we described. \u0000 \u0000In designing our BWT encoding and its lower bound, we also address the t-subset problem; here, the goal is to store a subset of t items drawn from a universe [1..n] using just lg (nt)+O(1) bits of space. A number of solutions to this basic problem are known, however encoding or decoding usually requires either O(t) operations on large integers [Knu05, Rus05] or O(n) operations. We provide a novel approach to reduce the encoding/decoding time to just O(t) operations on small integers (of size O(lg n) bits), without increasing the space required.","PeriodicalId":340112,"journal":{"name":"Workshop on Analytic Algorithmics and Combinatorics","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132906976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4