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Efficient quality review for modeling input dataset
"... Jackson, P. R. et al., Testing for bimodality in frequency distributions of data suggesting polymorphisms of drug metabolismhistograms and probit plots, Br. J. clin. Pharmac. (1989), 28, 647–653.3. Aarons, L. et al., Role of modelling and simulation in Phase I drug development.4. Purpose The poster ..."
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The poster’s purpose is to share our experiences and present our views on quality review for modeling input dataset (MID). We wish to encourage and enhance feedback and collaboration from colleagues.
How Sensitive is Processor Customization to the Workload’s Input Datasets?
"... Abstract — Hardware customization is an effective approach for meeting application performance requirements while achieving high levels of energy efficiency. Applicationspecific processors achieve high performance at low energy by tailoring their designs towards a specific workload, i.e., an applic ..."
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Cited by 4 (3 self)
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.e., an application or application domain of interest. A fundamental question that has remained unanswered so far though is to what extent processor customization is sensitive to the training workload’s input datasets. Current practice is to consider a single or only a few input datasets per workload during
The Effects of Different Climate Input Datasets on Simulated Carbon Dynamics in the Western Arctic
, 2007
"... simulations of carbon dynamics in the western Arctic (WALE region) were conducted during two recent decades by driving the Terrestrial Ecosystem Model (TEM) with three alternative climate datasets. Among the three TEM ..."
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Cited by 2 (1 self)
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simulations of carbon dynamics in the western Arctic (WALE region) were conducted during two recent decades by driving the Terrestrial Ecosystem Model (TEM) with three alternative climate datasets. Among the three TEM
Fitting a mixture model by expectation maximization to discover motifs in biopolymers.
 Proc Int Conf Intell Syst Mol Biol
, 1994
"... Abstract The algorithm described in this paper discovers one or more motifs in a collection of DNA or protein sequences by using the technique of expect~tiou ma.,dmization to fit a twocomponent finite mixture model to the set of sequences. Multiple motifs are found by fitting a mixture model to th ..."
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Cited by 947 (5 self)
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to the data, probabilistically erasing tile occurrences of the motif thus found, and repeating the process to find successive motifs. The algorithm requires only a set of unaligned sequences and a number specifying the width of the motifs as input. It returns a model of each motif and a threshold which
Automatic Subspace Clustering of High Dimensional Data
 Data Mining and Knowledge Discovery
, 2005
"... Data mining applications place special requirements on clustering algorithms including: the ability to find clusters embedded in subspaces of high dimensional data, scalability, enduser comprehensibility of the results, nonpresumption of any canonical data distribution, and insensitivity to the or ..."
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Cited by 724 (12 self)
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identical results irrespective of the order in which input records are presented and does not presume any specific mathematical form for data distribution. Through experiments, we show that CLIQUE efficiently finds accurate clusters in large high dimensional datasets.
BIRCH: an efficient data clustering method for very large databases
 In Proc. of the ACM SIGMOD Intl. Conference on Management of Data (SIGMOD
, 1996
"... Finding useful patterns in large datasets has attracted considerable interest recently, and one of the most widely st,udied problems in this area is the identification of clusters, or deusel y populated regions, in a multidir nensional clataset. Prior work does not adequately address the problem of ..."
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Cited by 576 (2 self)
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Finding useful patterns in large datasets has attracted considerable interest recently, and one of the most widely st,udied problems in this area is the identification of clusters, or deusel y populated regions, in a multidir nensional clataset. Prior work does not adequately address the problem
Estimating the Support of a HighDimensional Distribution
, 1999
"... Suppose you are given some dataset drawn from an underlying probability distribution P and you want to estimate a "simple" subset S of input space such that the probability that a test point drawn from P lies outside of S is bounded by some a priori specified between 0 and 1. We propo ..."
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Cited by 783 (29 self)
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Suppose you are given some dataset drawn from an underlying probability distribution P and you want to estimate a "simple" subset S of input space such that the probability that a test point drawn from P lies outside of S is bounded by some a priori specified between 0 and 1. We
Paradox lost? Firmlevel evidence on the returns to information systems.
 Manage Sci
, 1996
"... T he "productivity paradox" of information systems (IS) is that, despite enormous improvements in the underlying technology, the benefits of IS spending have not been found in aggregate output statistics.One explanation is that IS spending may lead to increases in product quality or varie ..."
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Cited by 465 (23 self)
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level data on several components of IS spending for 19871991. The dataset includes 367 large firms which generated approximately 1.8 trillion dollars in output in 1991.We supplemented the IS data with data on other inputs, output, and price deflators from other sources. As a result, we could assess several
Clustering Gene Expression Patterns
, 1999
"... Recent advances in biotechnology allow researchers to measure expression levels for thousands of genes simultaneously, across different conditions and over time. Analysis of data produced by such experiments offers potential insight into gene function and regulatory mechanisms. A key step in the ana ..."
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Cited by 451 (11 self)
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expression data. We define an appropriate stochastic error model on the input, and prove that under the conditions of the model, the algorithm recovers the cluster structure with high probability. The running time of the algorithm on an ngene dataset is O(n 2 (log(n)) c ). We also present a practical
Processing Digital Terrain Models By Regularized Spline With Tension: Tuning Interpolation Parameters for Different Input Datasets
, 2002
"... this paper we deal specifically with s.surf.rst. A specific feature of this method and its implementation in GRASS is a set of interpolation parameters providing flexibility in data processing. These parameters give the user a capability to process difficult datasets (e.g. photogrammetric, GPS and L ..."
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Cited by 1 (0 self)
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and LIDAR data), that can be hardly effectively processed by other conventional methods. As we show in the paper, the RST is capable of processing such datasets, but it usually requires good knowledge of the method and its parameters and preprocessing of input data is also needed
Results 1  10
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