Results 41 to 50 of about 9,313 (254)
Sensors, 2020 Due to the spectral complexity and high dimensionality of hyperspectral images (HSIs), the processing of HSIs is susceptible to the curse of dimensionality. In addition, the classification results of ground truth are not ideal. To overcome the problem of
Hong Liu +4 more
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Multi-classification for high-dimensional data using probabilistic neural networks
Journal of Radiation Research and Applied Sciences, 2022 Multi-classification tasks need sufficient information provided by the input data, whereas the input data lying in the high-dimensional space presents too sparse distributions to afford rich information, which creates trouble for multi-classification ...
Jingyi Li, Xiaojie Chao, Qin Xu
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Breaking the curse of dimensionality with Isolation Kernel
CoRR, 2021 The curse of dimensionality has been studied in different aspects. However, breaking the curse has been elusive. We show for the first time that it is possible to break the curse using the recently introduced Isolation Kernel. We show that only Isolation Kernel performs consistently well in indexed search, spectral & density peaks clustering, SVM ...
Kai Ming Ting +3 more
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Advanced Science, EarlyView.ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan +8 more
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Advanced Science, EarlyView.Through a systematic and comprehensive analysis of the environmental impacts for the emerging MXene synthesis pathways, this study presents process transformation and optimization opportunities for low‐carbon MXene production from laboratory to industrial scales.
Yushuai Huang +6 more
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Projection Methods and the Curse of Dimensionality
Journal of Mathematical Finance, 2018 We study the ability of three different projection methods to solve high-dimensional state space problems: Galerkin, collocation, and least squares projection. The curse of dimensionality can be reduced substantially for both Least Squares and Galerkin projection methods through the use of monomial formulas.
Heer, Burkhard, Maußner, Alfred
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A Data‐Driven Inverse Design Methodology for Magnetic Soft Millirobots Navigating in Confined Spaces
Advanced Science, EarlyView.A data‐efficient inverse design framework automates the optimization of magnetic soft millirobots for confined‐space navigation. Integrating a physics‐based Cosserat rod model with Bayesian optimization efficiently identifies high‐performance geometries.
Ziyu Ren +5 more
wiley +1 more source
A projection and density estimation method for knowledge discovery. [PDF]
PLoS ONE, 2012 A key ingredient to modern data analysis is probability density estimation. However, it is well known that the curse of dimensionality prevents a proper estimation of densities in high dimensions.
Adam Stanski, Olaf Hellwich
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Counting polycubes without the dimensionality curse
Discrete Mathematics, 2008 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gadi Aleksandrowicz, Gill Barequet
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Advanced Science, EarlyView.This review explores the convergence of artificial intelligence technologies in modeling drug–drug and drug–target interactions. By evaluating advanced feature engineering, architectural innovations, and learning paradigms reveals shared evolutionary trends and critical challenges, such as cold‐start settings and shortcut learning.
Xin Sun, Tong Wang
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