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Smoothed analysis of integer programming
Mathematical Programming, 2005zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Heiko Röglin, Berthold Vöcking
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To smooth or not to smooth? ROC analysis of perfusion fMRI data
Magnetic Resonance Imaging, 2005Blood oxygenation level dependent (BOLD) contrast has been widely used for visualizing regional neural activation. Temporal filtering and parameter estimation algorithms are generally used to account for the intrinsic temporal autocorrelation present in BOLD data.
Jiongjiong, Wang +3 more
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Smoothness analysis for trajectory features
1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2002Dynamic modeling of speech is potentially a major improvement on hidden Markov models (HMMs). In one approach, trajectory models are used to model the dynamics of the spectrum, and are used as basis for classification. Although some improvement has been achieved in this way, one would hope for more substantial improvements given that the independence ...
Zhihong Hu, Etienne Barnard
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Smoothed Analysis of Multiobjective Optimization
2009 50th Annual IEEE Symposium on Foundations of Computer Science, 2009We prove that the number of Pareto-optimal solutions in any multiobjective binary optimization problem with a finite number of linear objective functions is polynomial in the model of smoothed analysis. This resolves a conjecture of Rene Beier. Moreover, we give polynomial bounds on all finite moments of the number of Pareto-optimal solutions, which ...
Heiko Röglin, Shang-Hua Teng
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Smoothing methods for epidemiologic analysis
Statistics in Medicine, 1988AbstractThe development of techniques for fitting non‐parametric smooth curves has resulted in less restrictive regression models. We discuss the ideas underlying such smoothing algorithms, develop their application to epidemiologic studies and address specific issues, such as coping with correlated errors. An example illustrates a particular smoothing
M R, Segal +3 more
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An Analysis of General Exponential Smoothing
Operations Research, 1976General exponential smoothing and adaptive smoothing are terms used to describe the application of discounted least squares to the fitting of certain mathematical functions to time series data. The technique yields forecasts satisfying simple recursive equations that generally contain fairly complex terms.
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A Smoothed Perturbation Analysis of Parisian Options
IEEE Transactions on Automatic Control, 2015In this technical note we provide a smoothed perturbation analysis (SPA) estimator of the sensitivity of a discrete time Parisian option with respect to the barrier level. The analysis put forward is of interest in a broader context than that of exotic options as we provide an SPA analysis for a problem where the critical event for the SPA estimator is
Bernd Heidergott +2 more
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Communications of the ACM, 2009
This Gödel Prize-winning work traces the steps toward modeling real data.
Daniel A. Spielman, Shang-Hua Teng
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This Gödel Prize-winning work traces the steps toward modeling real data.
Daniel A. Spielman, Shang-Hua Teng
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1991
In previous chapters, notably in Chapters IV and V, we have used “synthetic arguments” at an informal level, trusting that the context would provide a meaning for the term “synthetic”, and would make the arguments themselves plausible. The aim of this final chapter is to make the notion of “synthetic reasoning” explicit, by setting up an axiomatic ...
Ieke Moerdijk, Gonzalo E. Reyes
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In previous chapters, notably in Chapters IV and V, we have used “synthetic arguments” at an informal level, trusting that the context would provide a meaning for the term “synthetic”, and would make the arguments themselves plausible. The aim of this final chapter is to make the notion of “synthetic reasoning” explicit, by setting up an axiomatic ...
Ieke Moerdijk, Gonzalo E. Reyes
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Smoothed Analysis of Algorithms and Heuristics
2005The theorists have long been challenged by the existence of remarkable algorithms and heuristics that are known by scientists and engineers to work well in practice, but whose theoretical analyses have been are negative or unconvincing. The root of the problem is that algorithms are usually analyzed in one of two ways: by worst-case or average-case ...
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