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143,267
PSO with Randomized LowDiscrepancy Sequences
"... We initialize a globalbest particle swarm with a Halton sequence, comparing it with uniform initialization on a range of benchmark function optimization problems. We see substantial improvements in performance, particularly with high complexity problems /small populations. Halton initialization yie ..."
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We initialize a globalbest particle swarm with a Halton sequence, comparing it with uniform initialization on a range of benchmark function optimization problems. We see substantial improvements in performance, particularly with high complexity problems /small populations. Halton initialization
Discrete LowDiscrepancy Sequences
, 2009
"... Holroyd and Propp used Hall’s marriage theorem to show that, given a probability distribution π on a finite set S, there exists an infinite sequence s1, s2,... in S such that for all integers k ≥ 1 and all s in S, the number of i in [1, k] with si = s differs from k π(s) by at most 1. We prove a gen ..."
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Cited by 2 (1 self)
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, and the work of Holroyd and Propp [8] on derandomized Markov chains. Here we focus on derandomizing something even more fundamental to probability theory: the notion of an independent sequence of discrete random variables. Key words: rotor router; discrepancy; quasirandom sequence; lowdiscrepancy sequence
Efficient similarity search in sequence databases
, 1994
"... We propose an indexing method for time sequences for processing similarity queries. We use the Discrete Fourier Transform (DFT) to map time sequences to the frequency domain, the crucial observation being that, for most sequences of practical interest, only the first few frequencies are strong. Anot ..."
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Cited by 505 (21 self)
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We propose an indexing method for time sequences for processing similarity queries. We use the Discrete Fourier Transform (DFT) to map time sequences to the frequency domain, the crucial observation being that, for most sequences of practical interest, only the first few frequencies are strong
A.: Improved Particle Swarm Optimization with Lowdiscrepancy Sequences
 In: IEEE Cong. on Evolutionary Computation (CEC 2008), Hong Kong (accepted, 2008
"... Abstract — Quasirandom or low discrepancy sequences, such as the Van der Corput, Sobol, Faure, Halton (named after their inventors) etc. are less random than a pseudorandom number sequences, but are more useful for computational methods which depend on the generation of random numbers. Some of these ..."
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Cited by 3 (3 self)
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Abstract — Quasirandom or low discrepancy sequences, such as the Van der Corput, Sobol, Faure, Halton (named after their inventors) etc. are less random than a pseudorandom number sequences, but are more useful for computational methods which depend on the generation of random numbers. Some
Maximum Likelihood Phylogenetic Estimation from DNA Sequences with Variable Rates over Sites: Approximate Methods
 J. Mol. Evol
, 1994
"... Two approximate methods are proposed for maximum likelihood phylogenetic estimation, which allow variable rates of substitution across nucleotide sites. Three data sets with quite different characteristics were analyzed to examine empirically the performance of these methods. The first, called ..."
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Cited by 540 (28 self)
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Two approximate methods are proposed for maximum likelihood phylogenetic estimation, which allow variable rates of substitution across nucleotide sites. Three data sets with quite different characteristics were analyzed to examine empirically the performance of these methods. The first, called the "discrete gamma model," uses several categories of rates to approximate the gamma distribution, with equal probability for each category. The mean of each category is used to represent all the rates falling in the category. The performance of this method is found to be quite good, and four such categories appear to be sufficient to produce both an optimum, or nearoptimum fit by the model to the data, and also an acceptable approximation to the continuous dis tribution. The second method, called "fixedrates mod el," classifies sites into several classes according to their rates predicted assuming the star tree. Sites in different classes are then assumed to be evolving at these fixed rates when other tree topologies are evaluated.
LowDiscrepancy Simulation
"... Summary. This article presents a survey of lowdiscrepancy sequences and their applications to quasiMonte Carlo methods for multidimensional numerical integration. QuasiMonte Carlo methods are deterministic versions of Monte Carlo methods which outperform Monte Carlo methods for many types of int ..."
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Summary. This article presents a survey of lowdiscrepancy sequences and their applications to quasiMonte Carlo methods for multidimensional numerical integration. QuasiMonte Carlo methods are deterministic versions of Monte Carlo methods which outperform Monte Carlo methods for many types
Initialising PSO with Randomised LowDiscrepancy Sequences: Some Preliminary and Comparative Results”, to appear
 in Proceedings of GECCO’2007
, 2007
"... Abstract — In this paper, we investigate the use of some welknown randomised lowdiscrepancy sequences (Halton, Sobol, and Faure sequences) for initialising particle swarms. We experimented with the standard globalbest particle swarm algorithm for function optimization on some benchmark problems, u ..."
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Cited by 1 (0 self)
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, using randomised lowdiscrepancy sequences for initialisation, and the results were compared with the same particle swarm algorithm using uniform initialisation with a pseudorandom generator. The results show that, the former initialisation method could help the particle swarm algorithm improve its
Fast Generation of LowDiscrepancy Sequences
 Journal of Computational and Applied Mathematics
, 1993
"... The paper presents a fast implementation of a constructive method to generate a special class of lowdiscrepancy sequences which are based on Van NeumannKakutani transformations. Such sequences can be used in various simulation codes where it is necessary to generate a certain number of uniformly ..."
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Cited by 13 (1 self)
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The paper presents a fast implementation of a constructive method to generate a special class of lowdiscrepancy sequences which are based on Van NeumannKakutani transformations. Such sequences can be used in various simulation codes where it is necessary to generate a certain number
Computational Investigation of LowDiscrepancy Sequences in . . .
 PROCEEDINGS OF THE SIXTEENTH ANNUAL CONFERENCE ON UNCERTAINTY IN ARTIFICIAL INTELLIGENCE (UAI2000)
, 2000
"... Monte Carlo sampling has become a major vehicle for approximate inference in Bayesian networks. In this paper, we investigate a family of related simulation approaches, known collectively as quasiMonte Carlo methods based on deterministic lowdiscrepancy sequences. We first ..."
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Cited by 14 (2 self)
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Monte Carlo sampling has become a major vehicle for approximate inference in Bayesian networks. In this paper, we investigate a family of related simulation approaches, known collectively as quasiMonte Carlo methods based on deterministic lowdiscrepancy sequences. We first
Results 1  10
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