Digital medicine and the curse of dimensionality by Visar Berisha, Chelsea Krantsevich, P. Richard Hahn, Shira Hahn, Gautam Dasarathy, Pavan Turaga, Julie Liss

“…This paper considers how the large number of features in vast digital health data can challenge the development of robust AI models—a phenomenon known as “the curse of dimensionality” in statistical learning theory. We provide an overview of the curse of dimensionality in the context of digital health, demonstrate how it can negatively impact out-of-sample performance, and highlight important considerations for researchers and algorithm designers.…”
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Approximate dynamic programming : solving the curses of dimensionality / by Powell, Warren B. 1955-

CNNs Avoid the Curse of Dimensionality by Learning on Patches by Vamshi C. Madala, Shivkumar Chandrasekaran, Jason Bunk

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Approximate Nearest Neighbor: Towards Removing the Curse of Dimensionality by Har-Peled, Sariel, Indyk, Piotr, Motwani, Rajeev

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Approximate Nearest Neighbor: Towards Removing the Curse of Dimensionality by Har-Peled, Sariel, Indyk, Piotr, Motwani, Rajeev

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Fractional Norms and Quasinorms Do Not Help to Overcome the Curse of Dimensionality by Evgeny M. Mirkes, Jeza Allohibi, Alexander Gorban

Subjects: “…curse of dimensionality…”
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A training strategy for hybrid models to break the curse of dimensionality. by Moein E Samadi, Sandra Kiefer, Sebastian Johaness Fritsch, Johannes Bickenbach, Andreas Schuppert

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A training strategy for hybrid models to break the curse of dimensionality by Moein E. Samadi, Sandra Kiefer, Sebastian Johaness Fritsch, Johannes Bickenbach, Andreas Schuppert

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An Investigation into the Relationship between Curse of Dimensionality and Dunning-Kruger Effect by Dr. Mehmet Cem Çatalbaş

“…The concept of confidence was examined via the relationship between two phenomena in the area of machine learning and psychology, namely the Dunning-Kruger effect and the curse of dimensionality. A relationship was established between these two phenomena which were investigated in the light of neuroscience. …”
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Detection Method for Randomly Generated User IDs: Lift the Curse of Dimensionality by Inwoo Ro, Boojoong Kang, Choonghyun Seo, Eul Gyu Im

“…The first is to avoid the curse of dimensionality with the compression of feature dimension size. …”
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Theory I: Why and When Can Deep Networks Avoid the Curse of Dimensionality? by Poggio, Tomaso, Mhaskar, Hrushikesh, Rosasco, Lorenzo, Miranda, Brando, Liao, Qianli

“…[formerly titled "Why and When Can Deep – but Not Shallow – Networks Avoid the Curse of Dimensionality: a Review"] The paper reviews and extends an emerging body of theoretical results on deep learning including the conditions under which it can be exponentially better than shallow learning. …”
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A model-based clustering via mixture of hierarchical models with covariate adjustment for detecting differentially expressed genes from paired design by Yixin Zhang, Wei Liu, Weiliang Qiu

Subjects: “…Curse of dimensionality…”
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Gene Expression-Based Cancer Classification for Handling the Class Imbalance Problem and Curse of Dimensionality by Sadam Al-Azani, Omer S. Alkhnbashi, Emad Ramadan, Motaz Alfarraj

“…Another common issue related to the gene expression dataset addressed in this paper is the curse of dimensionality. This problem is addressed by applying chi-square and information gain feature selection techniques. …”
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Why and when can deep-but not shallow-networks avoid the curse of dimensionality: A review by Mhaskar, Hrushikesh, Rosasco, Lorenzo, Miranda, Brando, Liao, Qianli, Poggio, Tomaso A

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Convergence Rate for a Curse-of-Dimensionality-Free Method for a Class of HJB PDEs by Kluberg, Lionel J., McEneaney, William M.

“…Although previous work indicated that the method was not subject to the curse-of-dimensionality, it did not indicate any error bounds or convergence rate. …”
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Challenging the Curse of Dimensionality in Multidimensional Numerical Integration by Using a Low-Rank Tensor-Train Format by Boian Alexandrov, Gianmarco Manzini, Erik W. Skau, Phan Minh Duc Truong, Radoslav G. Vuchov

“…This phenomenon is known as the curse of dimensionality and motivated the development of alternative methods such as the Monte Carlo method. …”
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Nearest neighbour imputation under single index models by Jun Shao, Lei Wang

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Fast simulation for multi-photon, atomic-ensemble quantum model of linear optical systems addressing the curse of dimensionality by Junpei Oba, Seiji Kajita, Akihito Soeda

“…Simulation is a promising tool to resolve this issue, but it must address the curse of dimensionality, namely, that the number of bases increases exponentially in the number of photons. …”
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A Full Tensor Decomposition Network for Crop Classification with Polarization Extension by Wei-Tao Zhang, Sheng-Di Zheng, Yi-Bang Li, Jiao Guo, Hui Wang

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A feature extraction method based on spectral segmentation and integration of hyperspectral images by Sayyed Hamed Alizadeh Moghaddam, Mehdi Mokhtarzade, Behnam Asghari Beirami

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