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Expectations and the Neutrality of Money
 JOURNAL OF ECONOMIC THEORY
, 1972
"... This paper provides a simple example of an economy in which equilibrium prices and quantities exhibit what may be the central feature of the modern business cycle: a systematic relation between the rate of change in nominal prices and the level of real output. The relationship, ..."
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Cited by 866 (5 self)
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This paper provides a simple example of an economy in which equilibrium prices and quantities exhibit what may be the central feature of the modern business cycle: a systematic relation between the rate of change in nominal prices and the level of real output. The relationship,
Decision theory – a simple example
, 2001
"... Decision theory is trivial, apart from computational details. You have a choice of various actions, a. The world may be in one of many states x; which one occurs may be influenced by your action. The world’s state is described by a probability distribution P (xa). Finally, there is a ..."
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Decision theory is trivial, apart from computational details. You have a choice of various actions, a. The world may be in one of many states x; which one occurs may be influenced by your action. The world’s state is described by a probability distribution P (xa). Finally, there is a
Decision Theory  a Simple Example
"... Introduction Decision theory is trivial, apart from computational details. You have a choice of various actions, a. The world may be in one of many states x; which one occurs may be influenced by your action. The world's state is described by a probability distribution P (xa). Finally, there ..."
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Introduction Decision theory is trivial, apart from computational details. You have a choice of various actions, a. The world may be in one of many states x; which one occurs may be influenced by your action. The world's state is described by a probability distribution P (xa). Finally, there is a utility function U(x, a) which specifies the payo# you receive when the world is in state x and you chose action a. The task of decision theory is to select the action that maximizes the expected utility, E [U a] = # d K x U(x, a)P (xa). (1) That's all. The computational problem is to maximize E [U a] over<F10
1 Preconditioning: Two Simple Examples
"... data interpolation with radial basis functions tend to become very illconditioned as the minimal separation distance qX between the data sites x 1,..., x N, is reduced. ..."
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data interpolation with radial basis functions tend to become very illconditioned as the minimal separation distance qX between the data sites x 1,..., x N, is reduced.
1. A Simple Example First
"... Abstract. We provide here a detailed proof of the fact that the two polynomials polU, polV, called P1 and P2 in Section 3.2 of the main article, admit unique power series solutions in [[x,t]] and [[y, t]], respectively. ..."
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Abstract. We provide here a detailed proof of the fact that the two polynomials polU, polV, called P1 and P2 in Section 3.2 of the main article, admit unique power series solutions in [[x,t]] and [[y, t]], respectively.
Superstars and Mediocrities: A Simple Example
"... Consider a competitive industry that combines workers with capital. There is free entry by rms, which each need one worker to operate one machine that has a rental cost of $4 million.1 All units of output are identical, and the amount of output that a
rm produces depends solely on the talent of its ..."
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Consider a competitive industry that combines workers with capital. There is free entry by rms, which each need one worker to operate one machine that has a rental cost of $4 million.1 All units of output are identical, and the amount of output that a
rm produces depends solely on the talent of its worker. There is an unlimited supply of potential workers with an outside wage of zero (outside meaning outside this industry). A novice is equally likely to produce anywhere between zero and one hundred units.2 The talent of a novice worker is unknown (including to himself) but becomes public knowledge after one period of work. Careers are
nite and last at most 16 periods. Workers cannot commit to decline higher outside wage o¤ers in the future. Industry output faces a downwardsloping demand curve, and the number of
rms is large,so that
rms take the market price as given and there is no aggregate uncertainty. Finally, for simplicity, there is no discounting. How does this market for talent work? That depends crucially on whether aspiring workers can pay for the opportunity to work. There are two extreme cases to consider. In the rst, individuals are constrained to take a nonnegative wage. This is the ine ¢ cient, but at the same time also the more straightforward case. In the second case, individuals
Very simple classification rules perform well on most commonly used datasets
 Machine Learning
, 1993
"... The classification rules induced by machine learning systems are judged by two criteria: their classification accuracy on an independent test set (henceforth "accuracy"), and their complexity. The relationship between these two criteria is, of course, of keen interest to the machin ..."
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Cited by 547 (5 self)
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to the machine learning community. There are in the literature some indications that very simple rules may achieve surprisingly high accuracy on many datasets. For example, Rendell occasionally remarks that many real world datasets have "few peaks (often just one) " and so are &
On the optimality of the simple Bayesian classifier under zeroone loss
 MACHINE LEARNING
, 1997
"... The simple Bayesian classifier is known to be optimal when attributes are independent given the class, but the question of whether other sufficient conditions for its optimality exist has so far not been explored. Empirical results showing that it performs surprisingly well in many domains containin ..."
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Cited by 818 (27 self)
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The simple Bayesian classifier is known to be optimal when attributes are independent given the class, but the question of whether other sufficient conditions for its optimality exist has so far not been explored. Empirical results showing that it performs surprisingly well in many domains
A Simple, Fast, and Accurate Algorithm to Estimate Large Phylogenies by Maximum Likelihood
, 2003
"... The increase in the number of large data sets and the complexity of current probabilistic sequence evolution models necessitates fast and reliable phylogeny reconstruction methods. We describe a new approach, based on the maximumlikelihood principle, which clearly satisfies these requirements. The ..."
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Cited by 2182 (27 self)
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. The core of this method is a simple hillclimbing algorithm that adjusts tree topology and branch lengths simultaneously. This algorithm starts from an initial tree built by a fast distancebased method and modifies this tree to improve its likelihood at each iteration. Due to this simultaneous adjustment
AgentSpeak(L): BDI Agents speak out in a logical computable language
, 1996
"... BeliefDesireIntention (BDI) agents have been investigated by many researchers from both a theoretical specification perspective and a practical design perspective. However, there still remains a large gap between theory and practice. The main reason for this has been the complexity of theoremprov ..."
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Cited by 514 (2 self)
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simple example. These derivations can then be used to prove the properties satis...
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