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Average Case Analysis of Algorithms on Sequences
TLDR
This book provides a unique overview of the tools and techniques used in average case analysis of algorithms.
Pairwise Alignment of Protein Interaction Networks
TLDR
This paper develops a framework for comprehensive alignment of PPI networks, inspired by duplication/divergence models that focus on understanding the evolution of protein interactions, and proposes a mathematical model that extends the concepts of match, mismatch, and gap in sequence alignment to that of match and duplication in network alignment and evaluates similarity between graph structures through a scoring function that accounts for evolutionary events.
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Analytical Depoissonization and its Applications
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Stability conditions for some distributed systems: buffered random access systems
  • W. Szpankowski
  • Mathematics, Computer Science
    Advances in Applied Probability
  • 1 June 1994
TLDR
This paper proves necessary and sufficient conditions for stability of the ALOHA system by means of a novel technique based on three simple observations: applying mathematical induction to a smaller copy of the system, isolating a single queue for which Loynes' stability criteria is adopted, and using stochastic dominance to verify the required stationarity assumptions in the Loyne criterion.
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An efficient algorithm for detecting frequent subgraphs in biological networks
TLDR
An innovative new algorithm for detecting frequently occurring patterns and modules in biological networks is presented, using an innovative graph simplification technique, which is ideally suited to biological networks.
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Compression of Graphical Structures: Fundamental Limits, Algorithms, and Experiments
TLDR
This paper proposes a two-stage compression algorithm that asymptotically achieves the structural entropy up to the nlog term (i.e., the first two leading terms) of theStructural entropy of G(n,p) is (n;2)h(p)-logn!+o(1)-nlog+O(n), which is the first provable (asymptotical) optimal graph compressor for Erdónyi graph models.
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On Pattern Frequency Occurrences in a Markovian Sequence
TLDR
exact and asymptotic formulae for moments, probability of r pattern occurrences for three different regions of r, namely: (i) r=O(1) , (ii) central limit regime, and (iii) large deviations regime are presented.
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Analysis of digital tries with Markovian dependency
TLDR
A complete characterization of a digital tree is presented from the depth viewpoint in a Markovian framework, that is, under the assumption that symbols in a key are Markov-dependent, and shows that D/sub n/ tends to the normal distribution in all cases except the symmetric independent model.
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A suboptimal lossy data compression based on approximate pattern matching
TLDR
For stationary mixing sequences, the problem investigated by Steinberg and Gutman by showing that a lossy extension of the Wyner-Ziv (1989) scheme cannot be optimal is settled, and the asymptotic behavior of the so-called approximate waiting time N/sub l/ is established.
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Asymptotic Behavior of the Lempel-Ziv Parsing Scheme and Digital Search Trees
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