Learning and transfer of measurement tasks.

These are the comparability of the transfer expressions be- tween studies utilizing different learning tasks, and the comparability of transfer measures at different stages of the learning of both the ... conditioned response’’; and (b) they yield a measure of transfer which is independent of variations in the rate of learning of different tasks em- ployed in transfer experiments, and thus permit comparisons ...

pmid:18905842 fatcat:hd6zacietzbtzb45o2wcwosnja

These are the comparability of the transfer expressions be- tween studies utilizing different learning tasks, and the comparability of transfer measures at different stages of the learning of both the ... conditioned response’’; and (b) they yield a measure of transfer which is independent of variations in the rate of learning of different tasks em- ployed in transfer experiments, and thus permit comparisons ...

doi:10.1037/h0061154 fatcat:glni6bxdbvdibbnghgcovfsi4y

., 1, 2) in which the interval between original learning of the training and transfer tasks was varied, thereby studying retention of transfer from Task I measured during acquisition of Task II. ... The present study differs in that retention of transfer is investigated by measuring recall and relearning of Task II. ...

This article focuses on a broad framing of the DARPA Transfer Learning Program research and an assessment of its progress, limitations, and challenges, from an admittedly personal but DARPA-influenced ... I will consider both indicated application areas for transfer learning, as well as indicated future research challenges. ... The DARPA TLP decided to measure transfer by comparing the learning of tasks A and B versus the learning of B alone. ...

doi:10.1609/aimag.v32i2.2337 fatcat:q4xkokudvjfmbplr4w7glmyjty

In this paper, we apply L_IT to compare and dissect information in datasets, evaluate representation models in transfer learning, and analyze catastrophic forgetting and continual learning algorithms. ... We propose a practical measure of the generalizable information in a neural network model based on prequential coding, which we term Information Transfer (L_IT). ... For example in experiments involving a Measuring Information Transfer in Transfer Learning The success of transfer learning depends on sharing knowledge from previous tasks [17] . ...

arXiv:2009.07624v2 fatcat:rlfo7tb44nhy5gh4jv3tabidm4

Multiple Versions

the transfer phase Use of brain activation and behavioral measures provides can provide a more accurate depiction of the learning process. ... Two different tasks orders, blocked and random, were used to test the effect of the practice schedule on the acquisition and transfer of 3D computer mazes. ... The content of the information herein does not necessarily reflect the position or the policy of the U.S. Government or the U.S. Army and no official endorsement should be inferred. ...

doi:10.1007/978-3-642-39454-6_40 fatcat:htoiajo6jreljfuozilyaamx3y

With the assumption of limited computational capacity, we obtain the observed phenomena -direct transfer and acceleration of learning -for increasing levels of task difficulty. ... The specificity of perceptual learning and the dichotomy between learning of 'easy' versus 'difficult' tasks have been assumed to involve different learning processes at different cortical areas. ... Jacobs, Dan Kersten, Scott Kirkpatrick, Mike Langer, Pascal Mamassian, Nestor Matthews, Suzanne McKee, John Oliensis, and Bosco Tjan for helpful comments and discussions. ...

doi:10.1016/s0042-6989(99)00140-6 pmid:10768045 fatcat:27j357b7f5hmjesmrkxxpfeecq

We introduce a new measure to evaluate the transferability of representations learned by classifiers. ... Our analysis shows that LEEP can predict the performance and convergence speed of both transfer and meta-transfer learning methods, even for small or imbalanced data. ... of how "close" θ and D are, and hence a measure of transferability. ...

arXiv:2002.12462v2 fatcat:vl36ctimzjgjhnebt3snudvk2e

Multiple Versions

A series of studies is reported examining specificity and transfer of learning in three very different tasks, including digit data entry, speeded aiming, and time production. ... (i.e., start or end of training), and the dependent measure used to assess performance (e.g., initiation time or execution time). ... Specificity and Transfer 5 Definitions and Contrasts Transfer and retention Transfer of learning is highly related to retention of learning. ...

doi:10.1016/b978-0-12-394293-7.00006-6 fatcat:skawdnve5be2jnzg7ce5t4tlp4

Most research has demonstrated learning of the trained task or even learning transfer to a closely related task. ... However, learning did not transfer to measures of language (reading and phonological awareness), as the PG and CG improved as much as the other trained groups. ... The characteristics of the trained tasks might also interfere with the transfer and specificity of learning [40] . ...

doi:10.1371/journal.pone.0135422 pmid:26267275 pmcid:PMC4534328 fatcat:duki5fgvkzf5npqyfldigvzute

DOAJ

Transfer learning and multi-task learning have been shown to improve performance for low-resource domains. ... Besides, we propose combining transfer learning and multi-task learning to improve the performance of biomedical named entity recognition systems, which is not applied before to the best of our knowledge ... Multi-task learning is a special case of transfer learning where multiple tasks are learned simultaneously [3] . ...

arXiv:2011.00425v1 fatcat:5tpxymmqfvanjm2pxmsscpphde

Open Access

We measured how learning in one task transferred to and so improved learning in a subsequent task. ... Here, we test the link between a memory being unstable, and the transfer of learning to a different type of memory task. ... Acknowledgments We are grateful to Daniel Wolpert for his thoughtful comments on aspects of the analysis of this work, and to the National Science Foundation (NSF; Division of Behavioral and Cognitive ...

doi:10.1016/j.cub.2015.11.035 pmid:26711493 pmcid:PMC5817890 fatcat:fqycmjrq4vfxth2ejsb553fyrq

Transfer learning aims to ameliorate this shortcoming by speeding up learning through the adaptation of previously learned behaviors in similar tasks. ... Instead of relying on a hand-coded inter-task mapping, this paper proposes a novel transfer learning method capable of autonomously creating an inter-task mapping by using a novel combination of sparse ... and Transfer Fitted-Q-Iteration (TrFQI), which makes use of a learned source task policy. ...

doi:10.1007/978-3-642-28499-1_2 fatcat:rvxgxa5awbfmvncaad3jo5jecu

If one experiment used number of correct responses as the measure of learning and found 50% transfer while a second experi- ment used number of trials to reach criterion as the measure of learning and ... If the measure of learning were num- ber of correct responses the formula would be: = E Percentage of tra a —— X 100. 4 4 TRANSFER DESIGNS AND FORMULAS If the measure of learning were num- ber of errors ...

pmid:13465925 fatcat:d3occvvacnh6llagaeq7q42yym

If one experiment used number of correct responses as the measure of learning and found 50% transfer while a second experi- ment used number of trials to reach criterion as the measure of learning and ... If the measure of learning were num- ber of correct responses the formula would be: = E Percentage of tra a —— X 100. 4 4 TRANSFER DESIGNS AND FORMULAS If the measure of learning were num- ber of errors ...

doi:10.1037/h0045180 fatcat:fsuzquvcjrhejgxdc2qgyvhwta

The measurement of transfer of training

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The measurement of transfer of training

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Page 445 of None Vol. 46, Issue 6 [page]

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Toward a Computational Model of Transfer

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Measuring Information Transfer in Neural Networks [article]

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Brain in the Loop Learning Using Functional Near Infrared Spectroscopy [chapter]

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Mechanisms of generalization in perceptual learning

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LEEP: A New Measure to Evaluate Transferability of Learned Representations [article]

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Specificity and Transfer of Learning [chapter]

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Generalization of Auditory Sensory and Cognitive Learning in Typically Developing Children

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Analyzing the Effect of Multi-task Learning for Biomedical Named Entity Recognition [article]

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Unstable Memories Create a High-Level Representation that Enables Learning Transfer

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Reinforcement Learning Transfer via Common Subspaces [chapter]

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Transfer designs and formulas

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Transfer designs and formulas

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