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- protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution...
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- application to evaluating segmentation algorithms and measuring ecological statistics...
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- Optimization: Algorithms to solve constrained and unconstrained continuous and discrete optimization problems. Statistics: Tools...
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- also shown to be good. An algorithm is also given that checks the primitivity ... portable C-code. It passed several stringent statistical tests, including diehard. Its speed is comparable ... merits are due to the efficient algorithms that are unique to polynomial calculations over...
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- type distribution via the EM algorithm, Scand. J. Statist...
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- GMRFs in complex hierarchical models, in which statistical inference is only possible using Markov Chain ... computational aspects, construct fast and reliable algorithms for MCMC inference, and provide an online ... ideal tool for researchers and students in statistics, particularly biostatistics and spatial statistics, as well...
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- privacy: the SuLQ framework. We consider a statistical database in which a trusted administrator introduces ... component analysis, k means clustering, the Perceptron Algorithm, the ID3 algorithm ... apparently!) all algorithms that operate in the in the statistical query learning model...
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- Mplus is a statistical modeling program that provides researchers with a flexible tool to analyze ... wide choice of models, estimators, and algorithms in a program that has an easy...
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- tuning and understanding simulation and optimization algorithms. Model-based investigations are common approaches in simulation ... strong need for sound statistical analysis of simulation and optimization algorithms. spot includes methods...
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- Optimization. QUESO is a collection of statistical algorithms and programming constructs supporting research into...
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- efficient algorithms for ICA (independent component analysis) employing HOS (higher order statistics), BSS (blind source...
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- development and performance evaluation of sparse matrix algorithms. It allows for robust and repeatable experiments ... quantum chemistry, chemical process simulation, mathematics and statistics, power networks, and other networks and graphs...
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- state-of-the-art message-passing algorithms and statistical routines for performing Bayesian inference...
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- intended to replace flexible statistical programming systems such as Matlab, Splus or R. Tetrad ... suite of principled search (”exploration,” ”discovery”) algorithms it provides--for example its ability to search...
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- python module that implements Bayesian statistical models and fitting algorithms, including Markov chain Monte Carlo...
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- estimated thanks to an EM algorithm. Adjusted tests statistics are derived, as well...