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Intrinsic dimensionality and small sample properties of classifiers [PDF]
, 1998 summary:Small learning-set properties of the Euclidean distance, the Parzen window, the minimum empirical error and the nonlinear single layer perceptron classifiers depend on an “intrinsic dimensionality” of the data, however the Fisher linear ...
Raudys, Šarūnas
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Dimensionality and fractals [PDF]
Chaos, Solitons & Fractals, 2002 15 pages ...
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ACM Transactions on Computational LogicArranging the bits of a random string or real into \( k \) columns of a 2D array or higher dimensional structure is typically accompanied with loss in the Kolmogorov complexity of the columns, which depends on
George Barmpalias, Xiaoyan Zhang
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On the dimensionality of behavior
Proceedings of the National Academy of Sciences, 2022 Significance How do we characterize animal behavior? Psychophysics started with human behavior in the laboratory, and focused on simple contexts, such as the decision among just a few alternative actions in response to sensory inputs.
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Data dimensionality estimation: Achievements and challanges [PDF]
, 2015 Dimensionality Reduction methods are effective preprocessing techniques that clustering algorithms can use for coping with high dimensionality. Dimensionality Reduction methods have the aim of projecting the original data set of dimensionality d ...
CAMASTRA, Francesco, Francesco Camastra
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Comparative Drug Response Profiling in Neuroblastoma Cell Lines and Patient‐Derived Tumor Organoids
Pediatric Blood &Cancer, EarlyView.ABSTRACT High‐risk neuroblastoma remains a leading cause of pediatric cancer mortality, and improved preclinical models are needed to guide therapeutic developments. We screened seven high‐risk neuroblastoma cell lines and three patient‐derived tumor organoids with 528 compounds alongside bone marrow controls, and compared them with external datasets ...
Krzysztof Wierbiłowicz +12 more
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Bifactor modelling and measurement invariance testing of the Innovative Behaviour Inventory
African Journal of Psychological Assessment, 2023 Innovation-driven growth demands that organisations periodically assess the innovative behaviour of employees and facilitate appropriate interventions to nurture it. Human behaviour is complex.
Hamfrey Sanhokwe +2 more
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Graph representation of multi-dimensional materials
JPhys MaterialsThe integration of graph-based representations with machine learning methodologies is transforming the landscape of material discovery, offering a flexible approach for modelling a variety of materials, from molecules and nanomaterials to expansive three-
Carina T Cai +2 more
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Bioengineering, 2022 Bone is a dynamic organ that can adapt its structure to meet the demands of its biochemical and biophysical environment. Osteocytes form a sensory network throughout the tissue and orchestrate tissue adaptation via the release of soluble factors such as ...
Robert T. Brady +2 more
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CoRR, 2017 We analyze a new approach to Machine Learning coming from a modification of classical regularization networks by casting the process in the time dimension, leading to a sort of collapse of dimensionality in the problem of learning the model parameters. This approach allows the definition of a online learning algorithm that progressively accumulates the
Marco Gori +2 more
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