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Titlebook: Maximum Entropy and Bayesian Methods; Boise, Idaho, USA, 1 Gary J. Erickson,Joshua T. Rychert,C. Ray Smith Conference proceedings 1998 Spri

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樓主: detumescence
21#
發(fā)表于 2025-3-25 06:36:25 | 只看該作者
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發(fā)表于 2025-3-25 11:24:07 | 只看該作者
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發(fā)表于 2025-3-25 21:54:10 | 只看該作者
Massive Inference and Maximum Entropy,ior was originally derived from the “monkey model” in which quanta of uniform intensity could appear randomly in the field of view. To avoid undue digitisation, the quanta had to be small, and this led to difficulties with the Law of Large Numbers, and to unavoidable approximations in computing the
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發(fā)表于 2025-3-26 01:44:13 | 只看該作者
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發(fā)表于 2025-3-26 08:14:35 | 只看該作者
Which Algorithms are Feasible? Maxent Approach,requires. The problem with the existing definitions of feasibility is that they are rather .. Our goal is to use the maximum entropy (MaxEnt) approach and get more motivated definitions..If an algorithm is feasible, then, intuitively, we would expect the following to be true: .., .....Thus, we can s
28#
發(fā)表于 2025-3-26 12:13:40 | 只看該作者
Maximum Entropy, Likelihood and Uncertainty: A Comparison,the first type, the objective is to estimate probability distributions given some moment conditions. In this case the ME and ML are equivalent. A generalization of this type of estimation models to incorporate noisy data is discussed as well. The second type of models encompasses the traditional lin
29#
發(fā)表于 2025-3-26 14:47:05 | 只看該作者
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