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AN INTRINSIC DIFFICULTY WITH INTERPOLATION ON THE BIDISK
"... Abstract. The set of possible values (w1,..., wk) = (f(x1),..., f(xk)) arising from restricting contractive elements f from some uniform algebra A to a finite set {x1,..., xk} in the domain is called an interpolation body. When the uniform algebra is the bidisk algebra, Cole and Wermer show that t ..."
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stronger notion of “computability ” follows which will allow us to discuss the intrinsic differences between interpolation on the bidisk and interpolation on the disk.
Estimating the Intrinsic Difficulty of A Recognition Problem
 Proceedings of the 12th International Conference on Pattern Recognition
, 1994
"... We describe an experiment in estimating the Bayes error of a concrete image classification problem: a difficult, practically important, twoclass character recognition problem. The Bayes error gives the "intrinsic difficulty" of the problem since it is the minimum error achievable by any ..."
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Cited by 4 (1 self)
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We describe an experiment in estimating the Bayes error of a concrete image classification problem: a difficult, practically important, twoclass character recognition problem. The Bayes error gives the "intrinsic difficulty" of the problem since it is the minimum error achievable by any
Eliciting Student Judgments of Intrinsic Difficulty for Understanding Misconceptions
, 2011
"... in Solving Basic Mathematics Problems Developmental mathematics students are one of the most challenging groups of students to work with. This particular group of students traditionally score lower on placement exams at the community college level. They have conceptions and ideas about how to solve ..."
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in Solving Basic Mathematics Problems Developmental mathematics students are one of the most challenging groups of students to work with. This particular group of students traditionally score lower on placement exams at the community college level. They have conceptions and ideas about how to solve an arithmetic problem presented to them. Some of the conceptions lead to solution strategies that result in correct answers. However, many of the students have misconceptions of solution strategies that
A MetaAnalytic Review of Experiments Examining the Effects of Extrinsic Rewards on Intrinsic Motivation
"... A metaanalysis of 128 studies examined the effects of extrinsic rewards on intrinsic motivation. As predicted, engagementcontingent, completioncontingent, and performancecontingent rewards significantly undermined freechoice intrinsic motivation (d =0.40,0.36, and0.28, respectively), as did ..."
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Cited by 602 (16 self)
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A metaanalysis of 128 studies examined the effects of extrinsic rewards on intrinsic motivation. As predicted, engagementcontingent, completioncontingent, and performancecontingent rewards significantly undermined freechoice intrinsic motivation (d =0.40,0.36, and0.28, respectively
Visual categorization with bags of keypoints
 In Workshop on Statistical Learning in Computer Vision, ECCV
, 2004
"... Abstract. We present a novel method for generic visual categorization: the problem of identifying the object content of natural images while generalizing across variations inherent to the object class. This bag of keypoints method is based on vector quantization of affine invariant descriptors of im ..."
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Cited by 984 (14 self)
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of image patches. We propose and compare two alternative implementations using different classifiers: Naïve Bayes and SVM. The main advantages of the method are that it is simple, computationally efficient and intrinsically invariant. We present results for simultaneously classifying seven semantic visual
Searching in metric spaces
, 2001
"... The problem of searching the elements of a set that are close to a given query element under some similarity criterion has a vast number of applications in many branches of computer science, from pattern recognition to textual and multimedia information retrieval. We are interested in the rather gen ..."
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Cited by 432 (38 self)
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presentations have been given for the same approaches. We present some basic results that explain the intrinsic difficulty of the search problem. This includes a quantitative definition of the elusive concept of “intrinsic dimensionality. ” We also present a unified
The Advantages of Evolutionary Computation
, 1997
"... Evolutionary computation is becoming common in the solution of difficult, realworld problems in industry, medicine, and defense. This paper reviews some of the practical advantages to using evolutionary algorithms as compared with classic methods of optimization or artificial intelligence. Specific ..."
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Cited by 536 (6 self)
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advantages include the flexibility of the procedures, as well as the ability to selfadapt the search for optimum solutions on the fly. As desktop computers increase in speed, the application of evolutionary algorithms will become routine. 1 Introduction Darwinian evolution is intrinsically a robust search
What Can Economists Learn from Happiness Research?
 FORTHCOMING IN JOURNAL OF ECONOMIC LITERATURE
, 2002
"... Happiness is generally considered to be an ultimate goal in life; virtually everybody wants to be happy. The United States Declaration of Independence of 1776 takes it as a selfevident truth that the “pursuit of happiness” is an “unalienable right”, comparable to life and liberty. It follows that e ..."
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Cited by 517 (24 self)
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that economics is – or should be – about individual happiness. In particular, the question is how do economic growth, unemployment and inflation, as well as institutional factors such as good governance, affect individual wellbeing? In addition to this intrinsic interest, there are three major reasons
Feature selection based on mutual information: Criteria of maxdepe ndency, maxrelevance, and minredundancy
 IEEE Trans. Pattern Analysis and Machine Intelligence
"... Abstract—Feature selection is an important problem for pattern classification systems. We study how to select good features according to the maximal statistical dependency criterion based on mutual information. Because of the difficulty in directly implementing the maximal dependency condition, we f ..."
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Cited by 533 (7 self)
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Abstract—Feature selection is an important problem for pattern classification systems. We study how to select good features according to the maximal statistical dependency criterion based on mutual information. Because of the difficulty in directly implementing the maximal dependency condition, we
Efficiently computing static single assignment form and the control dependence graph
 ACM TRANSACTIONS ON PROGRAMMING LANGUAGES AND SYSTEMS
, 1991
"... In optimizing compilers, data structure choices directly influence the power and efficiency of practical program optimization. A poor choice of data structure can inhibit optimization or slow compilation to the point that advanced optimization features become undesirable. Recently, static single ass ..."
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Cited by 997 (8 self)
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, the difficulty of their construction and their potential size have discouraged their use. We present new algorithms that efficiently compute these data structures for arbitrary control flow graphs. The algorithms use dominance frontiers, a new concept that may have other applications. We also give analytical
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