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Results 11 - 20
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7,554
A framework for mesencephalic dopamine systems based on predictive Hebbian learning
- J. Neurosci
, 1996
"... We develop a theoretical framework that shows how mesencephalic dopamine systems could distribute to their targets a signal that represents information about future expectations. In particular, we show how activity in the cerebral cortex can make predictions about future receipt of reward and how fl ..."
Abstract
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Cited by 385 (33 self)
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with physiological results for a subset of dopaminergic neurons located in the ventral tegmental area and surrounding dopaminergic neurons. The theory also makes testable predictions about human choice behavior on a simple decision-making task. Furthermore, we show that, through a simple influence on synaptic
Interactive Control of Avatars Animated with Human Motion Data
, 2002
"... Real-time control of three-dimensional avatars is an important problem in the context of computer games and virtual environments. Avatar animation and control is difficult, however, because a large repertoire of avatar behaviors must be made available, and the user must be able to select from this s ..."
Abstract
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Cited by 369 (38 self)
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this set of behaviors, possibly with a low-dimensional input device. One appealing approach to obtaining a rich set of avatar behaviors is to collect an extended, unlabeled sequence of motion data appropriate to the application. In this paper, we show that such a motion database can be preprocessed
Analysis of the impacts of distributed generation sources considering the appropriate choice of parameters in a multi-objective approach for distribution system planning
- In Proceedings of the 5th International Conference on European Electricity Market
, 2008
"... ABSTRACT Presence of distributed generation (DG) ..."
Large-scale simultaneous hypothesis testing: the choice of a null hypothesis
- JASA
, 2004
"... Current scientific techniques in genomics and image processing routinely produce hypothesis testing problems with hundreds or thousands of cases to consider simultaneously. This poses new difficulties for the statistician, but also opens new opportunities. In particular it allows empirical estimatio ..."
Abstract
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Cited by 301 (15 self)
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estimation of an appropriate null hypothesis. The empirical null may be considerably more dispersed than the usual theoretical null distribution that would be used for any one case considered separately. An empirical Bayes analysis plan for this situation is developed, using a local version of the false
A Test of the Efficiency of a Given Portfolio
- In Econometrica
, 1989
"... A test for the ex ante efficiency of a given portfolio of assets is analyzed. The relevant statistic has a tractable small sample distribution. Its power function is derived and used to study the sensitivity of the test to the portfolio choice and to the number of assets used to determine the ex pos ..."
Abstract
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Cited by 331 (14 self)
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A test for the ex ante efficiency of a given portfolio of assets is analyzed. The relevant statistic has a tractable small sample distribution. Its power function is derived and used to study the sensitivity of the test to the portfolio choice and to the number of assets used to determine the ex
Judgments of frequency and recognition memory in a multiple-trace memory model (Tech
- University of Oregon Cognitive Science Program
, 1986
"... The multiple-trace simulation model, MINERVA 2, was applied to a number of phenomena found in experiments on relative and absolute judgments of frequency, and forced-choice and yes-no recognition memory. How the basic model deals with effects of repetition, forgetting, list length, orientation task, ..."
Abstract
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Cited by 300 (3 self)
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The multiple-trace simulation model, MINERVA 2, was applied to a number of phenomena found in experiments on relative and absolute judgments of frequency, and forced-choice and yes-no recognition memory. How the basic model deals with effects of repetition, forgetting, list length, orientation task
QUALITY SERVICES FOR LIFE “QUALITY OF LIFE IS DETERMINED BY CHOICES. IT IS ESSENTIAL THAT WE GIVE OUR PEOPLE THE TOOLS TO BE AWARE AND TO MAKE THE MOST APPROPRIATE CHOICES, THUS EMPOWERING THEM TO EXPERIENCE THE MAXIMUM QUALITY OF LIFE”
, 2000
"... There are many people and organisations who deserve to be mentioned. We involved so many in this process over the last two and a half years and we thank everyone and every agency that contributed. Special mention needs to be given to some of the main players who went through the “grind ” from beginn ..."
Abstract
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There are many people and organisations who deserve to be mentioned. We involved so many in this process over the last two and a half years and we thank everyone and every agency that contributed. Special mention needs to be given to some of the main players who went through the “grind ” from beginning to end. These are not confined to but include:
Parameter Estimation Techniques: A Tutorial with Application to Conic Fitting
, 1995
"... Almost all problems in computer vision are related in one form or another to the problem of estimating parameters from noisy data. In this tutorial, we present what is probably the most commonly used techniques for parameter estimation. These include linear least-squares (pseudo-inverse and eigen a ..."
Abstract
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Cited by 278 (8 self)
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analysis); orthogonal least-squares; gradient-weighted least-squares; bias-corrected renormalization; Kalman filtering; and robust techniques (clustering, regression diagnostics, M-estimators, least median of squares). Particular attention has been devoted to discussions about the choice of appropriate
Lasso-type recovery of sparse representations for high-dimensional data
- ANNALS OF STATISTICS
, 2009
"... The Lasso is an attractive technique for regularization and variable selection for high-dimensional data, where the number of predictor variables pn is potentially much larger than the number of samples n. However, it was recently discovered that the sparsity pattern of the Lasso estimator can only ..."
Abstract
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Cited by 250 (14 self)
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that are induced by selecting small subsets of variables. Furthermore, a rate of convergence result is obtained on the ℓ2 error with an appropriate choice of the smoothing parameter. The rate is shown to be
Results 11 - 20
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7,554
