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Brain magnetic resonance imaging with contrast dependent on blood oxygenation.
 Proc. Natl. Acad. Sci. USA
, 1990
"... ABSTRACT Paramagnetic deoxyhemoglobin in venous blood is a naturally occurring contrast agent for magnetic resonance imaging (MRI). By accentuating the effects of this agent through the use of gradientecho techniques in high fields, we demonstrate in vivo images of brain microvasculature with imag ..."
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Cited by 648 (1 self)
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to regional neural activity. Magnetic resonance imaging (MRI) is a widely accepted modality for providing anatomical information. Current research (1) involves extending MRI methods to provide information about biological function, in addition to the concomitant anatomical information. In addition
Benchmarking Least Squares Support Vector Machine Classifiers
 NEURAL PROCESSING LETTERS
, 2001
"... In Support Vector Machines (SVMs), the solution of the classification problem is characterized by a (convex) quadratic programming (QP) problem. In a modified version of SVMs, called Least Squares SVM classifiers (LSSVMs), a least squares cost function is proposed so as to obtain a linear set of eq ..."
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Cited by 476 (46 self)
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In Support Vector Machines (SVMs), the solution of the classification problem is characterized by a (convex) quadratic programming (QP) problem. In a modified version of SVMs, called Least Squares SVM classifiers (LSSVMs), a least squares cost function is proposed so as to obtain a linear set
The Implementation of the Cilk5 Multithreaded Language
, 1998
"... The fifth release of the multithreaded language Cilk uses a provably good "workstealing " scheduling algorithm similar to the rst system, but the language has been completely redesigned and the runtime system completely reengineered. The efficiency of the new implementation was aided ..."
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Cited by 489 (28 self)
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, this "workfirst" principle has led to a portable Cilk5 implementation in which the typical cost of spawning a parallel thread is only between 2 and 6 times the cost of a C function call on a variety of contemporary machines. Many Cilk programs run on one processor with virtually no degradation
MetaCost: A General Method for Making Classifiers CostSensitive
 In Proceedings of the Fifth International Conference on Knowledge Discovery and Data Mining
, 1999
"... Research in machine learning, statistics and related fields has produced a wide variety of algorithms for classification. However, most of these algorithms assume that all errors have the same cost, which is seldom the case in KDD prob lems. Individually making each classification learner costsensi ..."
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Cited by 415 (4 self)
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functioning or change to it. Unlike stratification, MetaCost is applicable to any number of classes and to arbitrary cost matrices. Empirical trials on a large suite of benchmark databases show that MetaCost almost always produces large cost reductions compared to the costblind classifier used (C4.5RULES
Preferences over Inflation and Unemployment: Evidence from Surveys of Happiness
, 2000
"... This paper has two aims. The first is to show that citizens care about these two variables. We present evidence that inflation and unemployment belong in a wellbeing function. The second is to calculate the costs of inflation in terms of unemployment. We measure the relative size of the weights att ..."
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Cited by 469 (48 self)
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This paper has two aims. The first is to show that citizens care about these two variables. We present evidence that inflation and unemployment belong in a wellbeing function. The second is to calculate the costs of inflation in terms of unemployment. We measure the relative size of the weights
CALCULUS OF COST FUNCTIONS
"... Abstract. We study algebraic properties of cost functions. We give an application: building sets close to being Turing complete. 1. ..."
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Cited by 8 (5 self)
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Abstract. We study algebraic properties of cost functions. We give an application: building sets close to being Turing complete. 1.
Multiple kernel learning, conic duality, and the SMO algorithm
 In Proceedings of the 21st International Conference on Machine Learning (ICML
, 2004
"... While classical kernelbased classifiers are based on a single kernel, in practice it is often desirable to base classifiers on combinations of multiple kernels. Lanckriet et al. (2004) considered conic combinations of kernel matrices for the support vector machine (SVM), and showed that the optimiz ..."
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Cited by 445 (31 self)
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; moreover, the sequential minimal optimization (SMO) techniques that are essential in largescale implementations of the SVM cannot be applied because the cost function is nondifferentiable. We propose a novel dual formulation of the QCQP as a secondorder cone programming problem, and show how to exploit
Decomposing Global Cost Functions
"... Similarly to what has been done with Global Constraints in Constraint Programming, different results have been recently published on Global Cost Functions in weighted CSPs, defining the premises of a Cost Function Programming paradigm. In this paper, in the spirit of Bergeacyclic decompositions o ..."
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Cited by 2 (1 self)
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Similarly to what has been done with Global Constraints in Constraint Programming, different results have been recently published on Global Cost Functions in weighted CSPs, defining the premises of a Cost Function Programming paradigm. In this paper, in the spirit of Bergeacyclic decompositions
Cost Functions of Incomplete Markets
"... Incomplete markets without arbitrage opportunities are characterized by the existence of multiple risk neutral probabilities. A cost function describes the minimum value necessary for superhedging any claim and a wellknown property states that a cost function is necessarily the maximum of expectati ..."
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Incomplete markets without arbitrage opportunities are characterized by the existence of multiple risk neutral probabilities. A cost function describes the minimum value necessary for superhedging any claim and a wellknown property states that a cost function is necessarily the maximum
STOCHASTIC FRONTIER COST FUNCTION APPROACH.
"... translog stochastic frontier cost function approach ..."
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