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Model-based comparison of latency estimation methods for the pupillary light reflex. [PDF]
Sci RepSchepelmann M, Krojanski HG.
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An XGBoost-based predictive framework for diabetes mellitus multi-classification. [PDF]
Sci RepEl Sherbiny MM +4 more
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Sampling concerns in scanline algorithms
IEEE Transactions on Medical Imaging, 1997This paper investigates the problem of providing suitable interpolation for scanline algorithms. These algorithms are of interest, as they are parallelizable. A structure for analyzing the problem is given. The theory in regard to resampling is developed in the context of a scanline algorithm for image rotation.
Martin Fleury, Adrian F. Clark
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Proceedings of the thirty-third annual ACM symposium on Theory of computing, 2001
We develop a framework to study probabilistic sampling algorithms that approximate general functions of the form \genfunc, where \domain and \range are arbitrary sets. Our goal is to obtain lower bounds on the query complexity of functions, namely the number of input variables x_i that any sampling algorithm needs to query to approximate f(x_1,\ldots ...
Ziv Bar-Yossef +2 more
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We develop a framework to study probabilistic sampling algorithms that approximate general functions of the form \genfunc, where \domain and \range are arbitrary sets. Our goal is to obtain lower bounds on the query complexity of functions, namely the number of input variables x_i that any sampling algorithm needs to query to approximate f(x_1,\ldots ...
Ziv Bar-Yossef +2 more
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2000
Abstract Monte Carlo methods are an essential part of any practitioner’s toolkit when considering the approximation of integrals. Typically this will require the ability to generate from a wide variety of probability distributions. In fact, a major constraint on the implementation of Monte Carlo methods can be the lack of a suitable ...
Michael Evans, Tim Swartz
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Abstract Monte Carlo methods are an essential part of any practitioner’s toolkit when considering the approximation of integrals. Typically this will require the ability to generate from a wide variety of probability distributions. In fact, a major constraint on the implementation of Monte Carlo methods can be the lack of a suitable ...
Michael Evans, Tim Swartz
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Sampling algorithms in a stream operator
Proceedings of the 2005 ACM SIGMOD international conference on Management of data, 2005Complex queries over high speed data streams often need to rely on approximations to keep up with their input. The research community has developed a rich literature on approximate streaming algorithms for this application. Many of these algorithms produce samples of the input stream, providing better properties than conventional random sampling.
Theodore Johnson +2 more
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A fast algorithm for balanced sampling
Computational Statistics, 2006The authors propose a new implementation for the cube method of balanced sampling. In their algorithm the population data never has to be completely loaded in memory and remains in a file that can be read sequentially. So restrictions on the population size are relaxed. The execution time depends linearly on the population size.
Guillaume Chauvet, Yves Tillé
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