Rigid geometry solves "curse of dimensionality" effects in clustering methods: An application to omics data. [PDF]
PLoS One, 2017 Adachi S.
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The curse of dimensionality for the L-discrepancy with finite p
, 2023 Erich Novak, Friedrich Pillichshammer
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Factors influencing the nature of client complaint behaviour in the aftermath of adverse events
Veterinary Record, Volume 196, Issue 6, 15/22 March 2025.Abstract Background Negative veterinary client complaint behaviour poses wellbeing and reputational risks. Adverse events are one source of complaint. Identifying factors that influence adverse event‐related complaint behaviour is key to mitigating detrimental consequences and harnessing information that can be used to improve service quality, patient ...
Julie Gibson +3 more
wiley +1 more source
The curse of dimensionality: Animal-related risk factors for pediatric diarrhea in western Kenya, and methods for dealing with a large number of predictors. [PDF]
PLoS One, 2019 Meisner J, Mooney SJ, Rabinowitz PM.
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Rigid geometry solves “curse of dimensionality” effects in clustering methods: An application to omics data [PDF]
, 2016 Shun Adachi
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The Curse of Dense Low-Dimensional Information Retrieval for Large Index\n Sizes [PDF]
, 2020 Nils Reimers, Iryna Gurevych
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A Novel Flexible Kernel Density Estimator for Multimodal Probability Density Functions
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Estimating probability density functions (PDFs) is critical in data analysis, particularly for complex multimodal distributions. traditional kernel density estimator (KDE) methods often face challenges in accurately capturing multimodal structures due to their uniform weighting scheme, leading to mode loss and degraded estimation accuracy ...
Jia‐Qi Chen +5 more
wiley +1 more source
Towards breaking the curse of dimensionality in computational methods for the conformational analysis of molecules [PDF]
BMC Bioinformatics, 2014 Lie H.
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A Survey on Reinforcement Learning for Optimal Decision‐Making and Control of Intelligent Vehicles
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Reinforcement learning (RL) has been widely studied as an efficient class of machine learning methods for adaptive optimal control under uncertainties. In recent years, the applications of RL in optimised decision‐making and motion control of intelligent vehicles have received increasing attention.
Yixing Lan +5 more
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