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Learning Continuous Decomposable Models Using Mutual Information and Statistical Copulas. [PDF]
Entropy (Basel)Learning dependence graphs from multivariate continuous data is challenging when marginal distributions are heterogeneous, since likelihood-based nonparametric scores can be sensitive to smoothing choices and can confound marginal irregularities ...
Desuó Neto L +3 more
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The sustainability of recreational sports in Chinese cities based on cognitive entropy. [PDF]
PLoS OneWith progress of science and development of economy, increasing numbers of urban residents take part in recreational sports (RS) due to their more leisure time and increased income.
Zou X, Wang J, Zhang X, Zheng M, Chen H.
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Can Empirical Biplots Predict High Entropy Oxide Phases? [PDF]
Journal of Composites Science, 2021 High entropy oxides are entropy-stabilised oxides that adopt specific disordered structures due to entropy stabilisation. They are a new class of materials that utilises the high-entropy concept first discovered in metallic alloys. They can have interesting properties due to the interactions at the electronic level and can be combined with other ...
Leong, Z., Desai, P., Morley, N.
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Dimension-Free Empirical Entropy Estimation
IEEE Transactions on Information Theory, 2023 We seek an entropy estimator for discrete distributions with fully empirical accuracy bounds. As stated, this goal is infeasible without some prior assumptions on the distribution. We discover that a certain information moment assumption renders the problem feasible. We argue that the moment assumption is natural and, in some sense, {\em minimalistic} -
Doron Cohen +3 more
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Chernoff-Type Concentration of Empirical Probabilities in Relative Entropy [PDF]
IEEE Transactions on Information Theory, 2021 corrected a numerical ...
F. Richard Guo, Thomas S. Richardson
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Analysis of entropies based on empirical mode decomposition in amnesic mild cognitive impairment of diabetes mellitus [PDF]
Journal of Innovative Optical Health Sciences, 2015 EEG characteristics that correlate with the cognitive functions are important in detecting mild cognitive impairment (MCI) in T2DM. To investigate the complexity between aMCI group and age-matched non-aMCI control group in T2DM, six entropies combining ...
Dong Cui +5 more
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Empirical entropy, minimax regret and minimax risk [PDF]
Bernoulli, 2017 We consider the random design regression model with square loss. We propose a method that aggregates empirical minimizers (ERM) over appropriately chosen random subsets and reduces to ERM in the extreme case, and we establish sharp oracle inequalities for its risk. We show that, under the $\varepsilon^{-p}$ growth of the empirical $\varepsilon$-entropy,
Rakhlin, Alexander +2 more
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IEEE Access, 2021 For multidimensional data, Space-Filling Curves (SFCs) have been used to improve the execution time of spatial data queries. However, their effect on compression, when used to reorder the uncompressed values, is known to a lesser extent.
Conrad J. Haupt +2 more
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A Robust Machine Learning Model for Diabetic Retinopathy Classification
Journal of Imaging, 2023 Ensemble learning is a process that belongs to the artificial intelligence (AI) field. It helps to choose a robust machine learning (ML) model, usually used for data classification.
Gigi Tăbăcaru +3 more
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A Comparison of Empirical Tree Entropies [PDF]
, 2020 Whereas for strings, higher-order empirical entropy is the standard entropy measure, several different notions of empirical entropy for trees have been proposed in the past, notably label entropy, degree entropy, conditional versions of the latter two, and empirical entropy of trees (here, called label-shape entropy).
Hucke, Danny +2 more
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