نتایج جستجو برای: training feedback error fel

تعداد نتایج: 689476  

Journal: :Journal of neurophysiology 2015
Jinsung Wang Yuming Lei Jeffrey R Binder

The extent to which motor learning is generalized across the limbs is typically very limited. Here, we investigated how two motor learning hypotheses could be used to enhance the extent of interlimb transfer. According to one hypothesis, we predicted that reinforcement of successful actions by providing binary error feedback regarding task success or failure, in addition to terminal error feedb...

Journal: :ACM Transactions on Intelligent Systems and Technology 2021

In this article, we present a distributed variant of an adaptive stochastic gradient method for training deep neural networks in the parameter-server model. To reduce communication cost among workers and server, incorporate two types quantization schemes, i.e., weight quantization, into proposed Adam. addition, to bias introduced by operations, propose error-feedback technique compensate quanti...

Journal: :CoRR 2015
Andrew J. R. Simpson

Stochastic Gradient Descent (SGD) is arguably the most popular of the machine learning methods applied to training deep neural networks (DNN) today. It has recently been demonstrated that SGD can be statistically biased so that certain elements of the training set are learned more rapidly than others. In this article, we place SGD into a feedback loop whereby the probability of selection is pro...

The present study-both qualitative and quantitative--explored fifty EFL learners’ preferences for receiving error feedback on different grammatical units as well as their beliefs about teacher feedback strategies. The study also examined the effect of the students’ level of writing ability on their views about the importance of teacher feedback on different error types. Data was gathered throug...

Journal: :IEEE Transactions on Signal Processing 2017

Journal: :Neural Networks 1993
Hiroaki Gomi Mitsuo Kawato

This paper presents new learning schemes using feedback-error-learning for a neural network model applied to adaptive nonlinear feedback control. Feedback-error-learning was proposed as a learning method for forming a feedforward controller that uses the output of a feedback controller as the error for training a neural network model. Using new schemes for nonlinear feedback control, the actual...

Journal: :IJGBL 2017
Norah E. Dunbar Matthew L. Jensen Claude H. Miller Elena Bessarabova Yu-Hao Lee Scott N. Wilson Javier Elizondo Bradley J. Adame Joseph S. Valacich Sara K. Straub Judee K. Burgoon Brianna Lane Cameron W. Piercy David W. Wilson Shawn King Cindy Vincent Ryan M. Schuetzler

Oneof thebenefitsofusingdigitalgames foreducation is thatgamescanprovide feedback for learnerstoassesstheirsituationandcorrecttheirmistakes.Weconductedtwostudiestoexaminethe effectivenessofdifferentfeedbackdesign(timing,duration,repeats,andfeedbacksource)inaserious gamedesignedtoteachlearnersaboutcognitivebiases.Wealsocomparedthedigital...

2010
Stewart Craig Stephan Lewandowsky Daniel R. Little

Some current theories of probabilistic categorization assume that people gradually attenuate their learning in response to unavoidable error. However, existing evidence for this error discounting is sparse and open to alternative interpretations. We report two probabilistic-categorization experiments that investigated error discounting by shifting feedback probabilities to new values after diff...

Journal: :Optics express 2015
Marta Csatari Divall Patrick Mutter Edwin J Divall Christoph P Hauri

Intense ultrashort pulse lasers are used for fs resolution pump-probe experiments more and more at large scale facilities, such as free electron lasers (FEL). Measurement of the arrival time of the laser pulses and stabilization to the machine or other sub-systems on the target, is crucial for high time-resolution measurements. In this work we report on a single shot, spectrally resolved, non-c...

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