Results 11  20
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268
Bounded, minimal, and short representations of unit interval and unit circulararc graphs
"... We consider the unrestricted, minimal, and bounded representation problems for unit interval (UIG) and unit circulararc (UCA) graphs. In the unrestricted version, a proper circulararc (PCA) modelM is given and the goal is to obtain an equivalent UCA model U. We show a linear time algorithm with ne ..."
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that the previous linear time algorithm fails to provide a minimal model for some input graphs. We fix this algorithm but, unfortunately, it runs in linear space O(n2) time. Finally, we apply the minimal representation algorithms so as to find the minimum powers of paths and cycles that contain a given UIG and UCA
1The Cramér–Rao Bound for Sparse Estimation
"... The goal of this paper is to characterize the best achievable performance for the problem of estimating an unknown parameter having a sparse representation. Specifically, we consider the setting in which a sparsely representable deterministic parameter vector is to be estimated from measurements cor ..."
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corrupted by Gaussian noise, and derive a lower bound on the meansquared error (MSE) achievable in this setting. To this end, an appropriate definition of bias in the sparse setting is developed, and the constrained Cramér–Rao bound (CRB) is obtained. This bound is shown to equal the CRB of an estimator
Efficient Algorithms for the Electric Power Transaction Problem
"... Abstract. We present two efficient algorithms for solving the electric power transaction problem. The electric power transaction problem appears when maximizing the social benefit on electric power transactions among some private companies. The problem is a special case of the minimum cost flow prob ..."
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problem defined on a network with many leaves, where each leaf corresponds to a (private) company who wants to sell or buy electric power. Our first algorithm is based on the minimum mean cycle canceling algorithm and the second algorithm uses a linear time median finding algorithm. The first algorithm
Sorting Permutations by Reversals and Eulerian Cycle Decompositions 1
, 1997
"... Abstract We analyze the strong relationship among three combinatorial problems, namely the problem of sorting a permutation by the minimum number of reversals (MINSBR), the problem of finding the maximum number of edgedisjoint alternating cycles in a breakpoint graph associated with a given permut ..."
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Abstract We analyze the strong relationship among three combinatorial problems, namely the problem of sorting a permutation by the minimum number of reversals (MINSBR), the problem of finding the maximum number of edgedisjoint alternating cycles in a breakpoint graph associated with a given
The BKZ Simulation Algorithm
"... Hiermit versichere ich, die vorliegende BachelorThesis ohne Hilfe Dritter nur mit den angegebenen Quellen und Hilfsmitteln angefertigt zu haben. Alle Stellen, die aus Quellen entnommen wurden, sind als solche kenntlich gemacht. Diese Arbeit hat in gleicher oder ähnlicher Form noch keiner Prüfungsbe ..."
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. The BKZ simulation algorithm by Chen and Nguyen predicts the GramSchmidt norms of a lattice basis after a given time of rounds of BKZ reduction. Given the cost of the enumeration subroutine used in BKZ reduction, the simulation algorithm can also be used to estimate the running time of BKZ reduction
The flexibility of models of recognition memory: An analysis by the minimum description length principle
 Journal of Mathematical Psychology
, 2011
"... a b s t r a c t Ten continuous, discrete, and hybrid models of recognition memory are considered in the traditional paradigm with manipulation of response bias via baserates or payoff schedules. We present an efficient method for computing the Fisher information approximation (FIA) to the normalize ..."
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Cited by 2 (1 self)
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with virtual certainty. Note that if g dominates f , s m will be bounded from above for all m. Implementing this idea requires, for each model, a numerically stable means to evaluate the determinant of the Fisher information matrix even for extreme parameter values and a suitable proposal density g from which
1A SubNyquist Radar Prototype: Hardware and Algorithms
"... Abstract—Traditional radar sensing typically employs matched filtering between the received signal and the shape of the transmitted pulse. Matched filtering is conventionally carried out digitally, after sampling the received analog signals. Here, principles from classic sampling theory are generall ..."
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and implementation of a Xampling based hardware prototype that allows sampling of radar signals at rates much lower than Nyquist. We demonstrate by realtime analog experiments that our system is able to maintain reasonable recovery capabilities, while sampling radar signals that require sampling at a rate of about
Collection Tree Protocol
"... This paper presents and evaluates two principles for designing robust, reliable, and efficient collection protocols. These principles allow a protocol to benefit from accurate and agile link estimators by handling the dynamism such estimators introduce to routing tables. The first is datapath valida ..."
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validation: a protocol can use data traffic as active topology probes, quickly discovering and fixing routing loops. The second is adaptive beaconing: by extending the Trickle code propagation algorithm to routing control traffic, a protocol sends fewer beacons while simultaneously reducing its route repair
mirWIP: microRNA target prediction based on microRNAcontaining ribonucleoproteinenriched transcripts.
 Nat. Methods.
, 2008
"... Target prediction for animal microRNAs (miRNAs) has been hindered by the small number of verified targets available to evaluate the accuracy of predicted miRNAtarget interactions. Recently, a dataset of 3,404 miRNAassociated mRNA transcripts was identified by immunoprecipitation of the RNAinduce ..."
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Cited by 45 (5 self)
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, with the highest scores going to lin14 and hbl1, two of the first identified miRNA targets in C. elegans. Comparison of mirWIP performance to other methods We compared our algorithm to the three most commonly used target prediction methods for C. elegans: PicTAR 16 , TargetScanS 22 and miRanda 26 . We also
Results 11  20
of
268