Results 1 to 10 of about 137,983 (211)
On the analysis of movement smoothness [PDF]
Journal of NeuroEngineering and Rehabilitation, 2015 Quantitative measures of smoothness play an important role in the assessment of sensorimotor impairment and motor learning. Traditionally, movement smoothness has been computed mainly for discrete movements, in particular arm, reaching and circle drawing, using kinematic data.
Sivakumar Balasubramanian +3 more
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Comparing the Use of Measured and Smoothed Data in Forecasting Visual Field Tests Using Deep Learning [PDF]
Ophthalmology ScienceObjective: To evaluate the impact of training and testing deep learning (DL) models for visual field (VF) forecasting using input-target pairs in which the target is either the measured VF test result, or its smoothed counterpart constructed via linear ...
Ashkan Abbasi, PhD +7 more
doaj +2 more sources
A Friendly Smoothed Analysis of the Simplex Method [PDF]
SIAM Journal on Computing, 2020 Explaining the excellent practical performance of the simplex method for linear programming has been a major topic of research for over 50 years. One of the most successful frameworks for understanding the simplex method was given by Spielman and Teng (JACM `04), who developed the notion of smoothed analysis.
Daniel Dadush, Sophie Huiberts
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An Anti-Interference Demultiplexing Method for Electromagnetic Bessel Beams Carrying Orbital Angular Momentum [PDF]
SensorsThis work presents a simple yet effective anti-interference demultiplexing method for electromagnetic Bessel beams carrying orbital angular momentum (OAM), based on smoothed dynamic mode decomposition (smoothed DMD).
Congwei Mi +3 more
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Smoothed Analysis of Population Protocols.
CoRR, 2021 In this work, we initiate the study of \emph{smoothed analysis} of population protocols. We consider a population protocol model where an adaptive adversary dictates the interactions between agents, but with probability $p$ every such interaction may change into an interaction between two agents chosen uniformly at random.
Gregory Schwartzman, Yuichi Sudo
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Smoothed Analysis of the k-Means Method
Journal of the ACM, 2011 The k -means method is one of the most widely used clustering algorithms, drawing its popularity from its speed in practice. Recently, however, it was shown to have exponential worst-case running time.
Bodo Manthey, Heiko Roglin
exaly +3 more sources
Smoothed Analysis with Adaptive Adversaries [PDF]
2021 IEEE 62nd Annual Symposium on Foundations of Computer Science (FOCS), 2022 We prove novel algorithmic guarantees for several online problems in the smoothed analysis model. In this model, at each time step an adversary chooses an input distribution with density function bounded above pointwise by \(\tfrac{1}{\sigma }\) times that of the uniform distribution ...
Nika Haghtalab +2 more
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OS-PCA: Orthogonal Smoothed Principal Component Analysis Applied to Metabolome Data
Metabolites, 2021 Principal component analysis (PCA) has been widely used in metabolomics. However, it is not always possible to detect phenotype-associated principal component (PC) scores.
Hiroyuki Yamamoto +2 more
doaj +1 more source
Smoothed Shock Filtering: Algorithm and Applications
Journal of Imaging, 2021 This article presents the smoothed shock filter, which iteratively produces local segmentations in image’s inflection zones with smoothed morphological operators (dilations, erosions).
Antoine Vacavant
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Adversarial smoothed analysis [PDF]
Journal of Complexity, 2010 The purpose of this note is to extend the results on uniform smoothed analysis of condition numbers from \cite{BuCuLo:07} to the case where the perturbation follows a radially symmetric probability distribution. In particular, we will show that the bounds derived in \cite{BuCuLo:07} still hold in the case of distributions whose density has a ...
Felipe Cucker +2 more
openaire +4 more sources