An Improved Data-Driven Calibration Method with High Efficiency for a 6-DOF Hybrid Robot by Zhibiao Yan, Youyu Wang, Haitao Liu, Juliang Xiao, Tian Huang

“…Then, a large number of robot poses can be acquired in the whole workspace via a limited number of measurements, effectively solving the curse of dimensionality in measurement. (2) A mapping between the nominal joint variables and joint compensation values is established using a back propagation neural network (BPNN), which is trained directly using the measurement data through a unique algorithm involving inverse kinematics. …”
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Snake-Efficient Feature Selection-Based Framework for Precise Early Detection of Chronic Kidney Disease by Walaa N. Ismail

“…This approach helps mitigate the curse of dimensionality, reduce dimensionality, and enhance model performance. …”
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Study of Pricing of High-Dimensional Financial Derivatives Based on Deep Learning by Xiangdong Liu, Yu Gu

“…Thus, the deep learning-based method is used to overcome the “curse of dimensionality” caused by high-dimensional PDE with jump, and the numerical solution is obtained. …”
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FeaSel-Net: A Recursive Feature Selection Callback in Neural Networks by Felix Fischer, Alexander Birk, Peter Somers, Karsten Frenner, Cristina Tarín, Alois Herkommer

“…In order to cope with the curse of dimensionality in machine learning, it is necessary to reduce the overhead from irrelevant or redundant features. …”
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Accelerated modeling and design of a mixed refrigerant cryogenic process using a data-driven approach by Hosein Alimardani, Mehrdad Asgari, Roohangiz Shivaee-Gariz, Javad Tamnanloo

“…However, the curse of dimensionality and process design constraints pose significant hurdles for effective screening and optimization. …”
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Variational quantum algorithm for experimental photonic multiparameter estimation by Valeria Cimini, Mauro Valeri, Simone Piacentini, Francesco Ceccarelli, Giacomo Corrielli, Roberto Osellame, Nicolò Spagnolo, Fabio Sciarrino

“…Abstract Variational quantum metrology represents a powerful tool to optimize estimation strategies, resulting particularly beneficial for multiparameter estimation problems that often suffer from limitations due to the curse of dimensionality and computational complexity. To overcome these challenges, we develop a variational approach able to efficiently optimize a quantum multiphase sensor. …”
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On the enrichment of time series with textual data for forecasting agricultural commodity prices by Ivan José Reis Filho, Ricardo Marcondes Marcacini, Solange Oliveira Rezende

“…However, the existing representations have limitations, such as the curse of dimensionality and sparse data. This work investigates the finite use of domain-specific terms to investigate these problems by representing textual data with low dimensional space. …”
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Hybrid Tensor Networks for Fully Supervised and Semisupervised Hyperspectral Image Classification by Yahui Xiu, Fuyin Ye, Zhao Chen, Yuxuan Liu

“…The problems of the curse of dimensionality and spectral variability in HSIs can affect the efficiency of the classifier and cause the decline of the classification accuracy. …”
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Normalized effect size (NES): a novel feature selection model for Urdu fake news classification by Muhammad Wasim, Sehrish Munawar Cheema, Ivan Miguel Pires

“…TF-IDF transforms the textual data into a weighted term-document matrix and is usually prone to the curse of dimensionality. Our novel statistical model filters the most discriminative terms to reduce the data’s dimensionality and improve classification accuracy. …”
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Monte-Carlo planning in large POMDPs by Silver, David, Veness, Joel

“…First, Monte-Carlo sampling is used to break the curse of dimensionality both during belief state updates and during planning. …”
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Reinforcement Learning in Multidimensional Environments Relies on Attention Mechanisms by Niv, Yael, Daniel, Reka, Geana, Andra, Gershman, Samuel J., Leong, Yuan Chang, Radulescu, Angela, Wilson, Robert C.

“…In this way, cortical attention mechanisms interact with learning in the basal ganglia to solve the “curse of dimensionality” in reinforcement learning.…”
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Reduced models for sparse grid discretizations of the multi-asset Black-Scholes equation by Gómez, Pablo, Bungartz, Hans-Joachim, Peherstorfer, Benjamin

“…We therefore rely on sparse grid discretizations of the PDEs, which allow us to cope with the curse of dimensionality to some extent. We then derive reduced models with proper orthogonal decomposition. …”
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Multifidelity Information Fusion Algorithms for High-Dimensional Systems and Massive Data sets by Venturi, Daniele, Perdikaris, Paris, Karniadakis, George E

“…Hence, we tackle simultaneously the “big N" problem for big data and the curse of dimensionality in multivariate parametric problems. …”
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Modern challenges in distribution testing by Kamath, Gautam (Gautam Chetan)

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Testing Ising Models by Daskalakis, Constantinos, Dikkala, Sai Nishanth

“…We demonstrate that, in this structured setting, we can avoid the curse of dimensionality, obtaining sample, and time efficient testers for independence and goodness-of-fit. …”
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Low-Dimensional Statistics of Anatomical Variability via Compact Representation of Image Deformations by Zhang, Miaomiao, Wells, William M., Golland, Polina

“…Using image-based descriptors to investigate clinical hypotheses and therapeutic implications is challenging due to the notorious “curse of dimensionality” coupled with a small sample size. …”
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Testing ising models by Daskalakis, C, Dikkala, N, Kamath, G

“…We demonstrate that, in this structured setting, we can avoid the curse of dimensionality, obtaining sample and time efficient testers for independence and goodness-of-fit. …”
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The Big Data Newsvendor: Practical Insights from Machine Learning Analysis by Rudin, Cynthia, Vahn, Gah-Yi

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mCENTRIST : a multi-channel feature generation by Xiao, Yang, Wu, Jianxin, Yuan, Junsong

“…In order to avoid the curse of dimensionality, tradeoffs at both feature and channel levels have been executed to make mCENTRIST computationally practical. …”
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Towards scalable synthesis of stochastic control systems by Zamani, M, Tkachev, I, Abate, A

“…A fundamental issue with the existing techniques is the known “curse of dimensionality,” which is due to the need to discretize state and input sets. …”