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Efficient Approximate Algorithms for Empirical Entropy and Mutual Information
Proceedings of the 2021 International Conference on Management of Data, 2021Empirical entropy is a classic concept in data mining and the foundation of many other important concepts like mutual information. However, computing the exact empirical entropy/mutual information on large datasets can be expensive. Some recent research work explores sampling techniques on the empirical entropy/mutual information to speed up the top-k ...
Xingguang Chen, Sibo Wang 0001
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Fast Approximation of Empirical Entropy via Subsampling
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019Empirical entropy refers to the information entropy calculated from the empirical distribution of a dataset. It is a widely used aggregation function for knowledge discovery, as well as the foundation of other aggregation functions such as mutual information.
Chi Wang 0001, Bailu Ding
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and empirical measures, the irregular set and entropy
Ergodic Theory and Dynamical Systems, 2023AbstractFor integers a and $b\geq 2$ , let $T_a$ and $T_b$ be multiplication by a and b on $\mathbb {T}=\mathbb {R}/\mathbb {Z}$ . The action on $\mathbb {T}$ by $T_a$ and $T_b$ is called $\times a,\times b$ action and it is known that, if a and b are multiplicatively independent, then the only $\times a,\times b$ invariant and ergodic ...
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Empirical entropy for right censored data
Acta Mathematicae Applicatae Sinica, English Series, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhao, Guo-qing, Liang, Wei, He, Shu-yuan
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How changes affect software entropy: an empirical study
Empirical Software Engineering, 2012Context Software systems continuously change for various reasons, such as adding new features, fixing bugs, or refactoring. Changes may either increase the source code complexity and disorganization, or help to reducing it. Aim This paper empirically investigates the relationship of source code complexity and disorganization--measured using source code
Gerardo Canfora +3 more
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An Empirical Test of Sokolov's Entropy Model of the Orienting Response
Psychophysiology, 1974ABSTRACTSeveral hypotheses, most of them deduced from Sokolov's entropy model of the Orienting Response (OR), were tested. The Galvanic Skin Response (GSR) served as the indicator of the OR. Printed language, analyzed with regard to the information content in bits, was used as stimulus material. Forty‐eight female students served as subjects.
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Empirical Scale of Side-Chain Conformational Entropy in Protein Folding
Journal of Molecular Biology, 1993A major effect in the energetics of protein folding is the loss of conformational entropy of the side-chains. The definition of entropy as the Boltzmann sampling over all states (S = -R sigma p(i) ln p(i)) requires evaluation of the probability (p(i)) of the system being in rotameric state i. The principle of this paper is to obtain an estimate of p(i)
S D, Pickett, M J, Sternberg
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Blockwise empirical entropy tests for time series regressions
Journal of Time Series Analysis, 2005Abstract. This paper shows how the empirical entropy (also known as exponential likelihood or non‐parametric tilting) method can be used to test general parametric hypothesis in time series regressions. To capture the weak dependence of the observations, the paper uses blocking techniques which are also used in the bootstrap literature on time series.
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Functional limit theorems and empirical entropy. II
1987This paper is a continuation of the author's article ibid. 33, 35-45 (1986; Zbl 0627.60043); translation from Teor. Veroyatn. Mat. Stat. 33, 31-42 (1985). It contains the second half of the proofs of the theorems presented in part I.
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