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No Free Lunch Theorems for Optimization
, 1997
"... A framework is developed to explore the connection between effective optimization algorithms and the problems they are solving. A number of “no free lunch ” (NFL) theorems are presented which establish that for any algorithm, any elevated performance over one class of problems is offset by performan ..."
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Cited by 961 (10 self)
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A framework is developed to explore the connection between effective optimization algorithms and the problems they are solving. A number of “no free lunch ” (NFL) theorems are presented which establish that for any algorithm, any elevated performance over one class of problems is offset
No Free Lunch Theorems for Search
, 1995
"... We show that all algorithms that search for an extremum of a cost function perform exactly the same, when averaged over all possible cost functions. In particular, if algorithm A outperforms algorithm B on some cost functions, then loosely speaking there must exist exactly as many other functions wh ..."
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Cited by 292 (2 self)
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We show that all algorithms that search for an extremum of a cost function perform exactly the same, when averaged over all possible cost functions. In particular, if algorithm A outperforms algorithm B on some cost functions, then loosely speaking there must exist exactly as many other functions where B outperforms A. Starting from this we analyze a number of the other a priori characteristics of the search problem, like its geometry and its informationtheoretic aspects. This analysis allows us to derive mathematical benchmarks for assessing a particular search algorithm 's performance. We also investigate minimax aspects of the search problem, the validity of using characteristics of a partial search over a cost function to predict future behavior of the search algorithm on that cost function, and timevarying cost functions. We conclude with some discussion of the justifiability of biologicallyinspired search methods.
No Free Lunch For Noise Prediction
"... No Free Lunch theorems have shown that learning algorithms cannot be universally good. We show that No Free Lunch 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 u ..."
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Cited by 1 (0 self)
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No Free Lunch theorems have shown that learning algorithms cannot be universally good. We show that No Free Lunch 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
No Free Lunch in Data Privacy
"... Differential privacy is a powerful tool for providing privacypreserving noisy query answers over statistical databases. It guarantees that the distribution of noisy query answers changes very little with the addition or deletion of any tuple. It is frequently accompanied by popularized claims that i ..."
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Cited by 78 (6 self)
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that it provides privacy without any assumptions about the data and that it protects against attackers who know all but one record. In this paper we critically analyze the privacy protections offered by differential privacy. First, we use a nofreelunch theorem, which defines nonprivacy as a game, to argue
No Free Lunch in the Search for Creativity
"... We consider computational creativity as a search process and give a No Free Lunch result for computational creativity in this context. That is, we show that there is no a priori “best ” creative strategy. We discuss some implications of this result and suggest some additional questions to be explore ..."
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Cited by 2 (0 self)
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We consider computational creativity as a search process and give a No Free Lunch result for computational creativity in this context. That is, we show that there is no a priori “best ” creative strategy. We discuss some implications of this result and suggest some additional questions
The No Free Lunch and Problem Description Length
 Proceedings of the Genetic and Evolutionary Computation Conference (GECCO2001
, 2001
"... The No Free Lunch theorem is reviewed and cast within a simple framework for blackbox search. A duality result which relates functions being optimized to algorithms optimizing them is obtained and is used to sharpen the No Free Lunch theorem. Observations are made concerning problem descriptio ..."
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Cited by 53 (5 self)
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The No Free Lunch theorem is reviewed and cast within a simple framework for blackbox search. A duality result which relates functions being optimized to algorithms optimizing them is obtained and is used to sharpen the No Free Lunch theorem. Observations are made concerning problem
No freelunch and bayesian optimality
 IJCNN Workshop on MetaLearning
, 2007
"... We take a Bayesian approach to the issues of bias, meta bias, transfer, overfit, and NoFreeLunch in the context of supervised learning. If we accept certain relationships between the function class, on training set data, and off training set data, then a graphical model can be created that represe ..."
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Cited by 6 (2 self)
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We take a Bayesian approach to the issues of bias, meta bias, transfer, overfit, and NoFreeLunch in the context of supervised learning. If we accept certain relationships between the function class, on training set data, and off training set data, then a graphical model can be created
No Free Lunch and Benchmarks
"... We extend previous results concerning BlackBox search algorithms, presenting new theoretical tools related to No Free Lunch (NFL) where functions are restricted to some Benchmark (that need not be permutation closed), algorithms are restricted to some collection (that need not be permutation closed ..."
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Cited by 1 (0 self)
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We extend previous results concerning BlackBox search algorithms, presenting new theoretical tools related to No Free Lunch (NFL) where functions are restricted to some Benchmark (that need not be permutation closed), algorithms are restricted to some collection (that need not be permutation
Reinterpreting no free lunch
 Evolutionary Computation
"... Since it’s inception, the “No Free Lunch theorem ” 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 fro ..."
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Cited by 7 (2 self)
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Since it’s inception, the “No Free Lunch theorem ” 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
Results 1  10
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608