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Development of a Parsimonious Set of Citylevel Environmental Performance
"... Abstract The potential tradeoff between the twin goals of reducing environmental impact while maintaining growth will require China's cities to evaluate the economic impact of urban pollution at the local level. Using economic inputoutput analysis, city level indicators of economic activity a ..."
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of Jiyuan, a small city in Henan province, we demonstrate a method for local public agencies to facilitate administrative tracking of monetized air pollution based on underlying economic activity, and outline a minimum set of metrics which a small city in China must track in order to estimate the monetized
LongTerm Prediction of Time Series using a Parsimonious Set of Inputs and LSSVM
"... Abstract. Time series prediction is an important problem in many areas of science and engineering. We investigate the use of a parsimonious set of autoregressive variables in the longterm prediction task using the direct prediction approach. We use a fast input selection algorithm on a large set of ..."
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Cited by 2 (0 self)
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Abstract. Time series prediction is an important problem in many areas of science and engineering. We investigate the use of a parsimonious set of autoregressive variables in the longterm prediction task using the direct prediction approach. We use a fast input selection algorithm on a large set
Least angle regression
, 2004
"... The purpose of model selection algorithms such as All Subsets, Forward Selection and Backward Elimination is to choose a linear model on the basis of the same set of data to which the model will be applied. Typically we have available a large collection of possible covariates from which we hope to s ..."
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Cited by 1326 (37 self)
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to select a parsimonious set for the efficient prediction of a response variable. Least Angle Regression (LARS), a new model selection algorithm, is a useful and less greedy version of traditional forward selection methods. Three main properties are derived: (1) A simple modification of the LARS algorithm
A Simple, Fast, and Accurate Algorithm to Estimate Large Phylogenies by Maximum Likelihood
, 2003
"... The increase in the number of large data sets and the complexity of current probabilistic sequence evolution models necessitates fast and reliable phylogeny reconstruction methods. We describe a new approach, based on the maximumlikelihood principle, which clearly satisfies these requirements. The ..."
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Cited by 2182 (27 self)
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of distancebased and parsimony approaches. The reduction of computing time is dramatic in comparison with other maximumlikelihood packages, while the likelihood maximization ability tends to be higher. For example, only 12 min were required on a standard personal computer to analyze a data set consisting
Parsimonious Neurofuzzy
, 1996
"... this paper. Another important issue when constructing models from empirical data, is the quality of this data. Ideally this data should be well distributed and noise free, two unrealistic demands (especially in high dimensions). A common approach to these problems in both statistical and neural netw ..."
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network communities is regularisation, which penalises the weight training cost function to try and control superfluous parameters. Despite building parsimonious models, due to the poor quality of the training set some weights maybe be poorly identified, producing models that generalise badly
Parsimonious Labeling
"... We propose a new family of discrete energy minimization problems, which we call parsimonious labeling. Our energy function consists of unary potentials and highorder clique potentials. While the unary potentials are arbitrary, the clique potentials are proportional to the diversity of the set of u ..."
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We propose a new family of discrete energy minimization problems, which we call parsimonious labeling. Our energy function consists of unary potentials and highorder clique potentials. While the unary potentials are arbitrary, the clique potentials are proportional to the diversity of the set
Parsimonious flooding in dynamic graphs
 In Proc. of 28th Symp. on Principles of Distributed Computing (PODC
, 2009
"... An edgeMarkovian process with birthrate p and deathrate q generates sequences of graphs (G0, G1, G2,...) with the same node set [n] such that Gt is obtained from Gt−1 as follows: if e / ∈ E(Gt−1) then e ∈ E(Gt) with probability p, and if e ∈ E(Gt−1) then e / ∈ E(Gt) with probability q. Clementi e ..."
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Cited by 37 (1 self)
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An edgeMarkovian process with birthrate p and deathrate q generates sequences of graphs (G0, G1, G2,...) with the same node set [n] such that Gt is obtained from Gt−1 as follows: if e / ∈ E(Gt−1) then e ∈ E(Gt) with probability p, and if e ∈ E(Gt−1) then e / ∈ E(Gt) with probability q. Clementi
Y: Haplotype inference by maximum parsimony
 Bioinformatics
"... Motivation: Haplotypes have been attracting increasing attention because of their importance in analysis of many finescale moleculargenetics data. Since direct sequencing of haplotype via experimental methods is both timeconsuming and expensive, haplotype inference methods that infer haplotypes b ..."
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Cited by 64 (4 self)
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based on genotype samples become attractive alternatives. Results: (1) We design and implement an algorithm for an important computational model of haplotype inference that has been suggested before in several places. The model finds a set of minimum number of haplotypes that explains the genotype
Islands of Tractability for Parsimony Haplotyping
 Proc. IEEE Computational Systems Bioinformatics Conf
, 2005
"... We study the parsimony approach to haplotype inference, which calls for finding a set of haplotypes of minimum cardinality that explains an input set of genotypes. We prove that the problem is APXhard even in very restricted cases. On the positive side, we identify islands of tractability for the p ..."
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Cited by 13 (2 self)
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We study the parsimony approach to haplotype inference, which calls for finding a set of haplotypes of minimum cardinality that explains an input set of genotypes. We prove that the problem is APXhard even in very restricted cases. On the positive side, we identify islands of tractability
The Contest Between Parsimony and Likelihood
"... In a “classic ” phylogenetic inference problem, the observed taxa are assumed to be the leaves of a bifurcating tree and the goal is to infer just the “topology ” of the tree (i.e., the formal tree structure linking the extant taxa at the tips), not amount of time between branching events, or amount ..."
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Cited by 18 (0 self)
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, or amount of evolution that has taken place on branches, or character states of interior vertices. Two of the main methods that biologists now use to solve such problems are maximum likelihood (ML) and maximum parsimony (MP); distance methods constitute a third approach, which will not be discussed here. ML
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