No free lunch but a cheaper supper: A general framework for streaming anomaly detection
نویسندگان
چکیده
منابع مشابه
Reinterpreting No Free Lunch
Abstract Since its inception, the "No Free Lunch" theorem (NFL) has concerned the application of symmetry results rather than the symmetries themselves. In our view, the conflation of result and application obscures the simplicity, generality, and power of the symmetries involved. This paper separates result from application, focusing on and clarifying the nature of underlying symmetries. The r...
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Some philosophers (see (Armstrong, 1997), (Cameron, 2008), (Melia, 2005), and (Schaffer, 2007, 2009, 2010a)) have recently suggested that explanations of a certain sort can mitigate our ontological commitments. The explanations in question, grounding explanations, are those that tell us what it is in virtue of which an entity exists and has the features it does. These philosophers claim that th...
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conomists love to say that there is no such thing as a free lunch. But the Chilean government agency responsible for school grants, Junta Nacional de Auxilio Escolar y Becas (JUNAEB), is an exception to the rule. During the school year, JUNAEB provides breakfast and lunch for 2 million children in primary and secondary public schools. In a developing country where about 14 percent of children u...
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A framework is developed to explore the connection between e ective optimization algorithms and the problems they are solving A number of no free lunch NFL theorems are presented that establish that for any algorithm any elevated performance over one class of problems is exactly paid for in performance over another class These theorems result in a geometric interpretation of what it means for a...
متن کاملNo Free Lunch for Noise Prediction
No-free-lunch theorems have shown that learning algorithms cannot be universally good. We show that no free funch exists for noise prediction as well. We show that when the noise is additive and the prior over target functions is uniform, a prior on the noise distribution cannot be updated, in the Bayesian sense, from any finite data set. We emphasize the importance of a prior over the target f...
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ژورنال
عنوان ژورنال: Expert Systems with Applications
سال: 2020
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2020.113453