The multi-output Gaussian process ($\mathcal{MGP}$) is based on the assumption that outputs share commonalities, however, if this does not hold negative transfer will lead to decreased performance relative learning independently or in subsets. In article, we first define context of an $\mathcal{MGP}$ and then derive necessary conditions for model avoid transfer. Specifically, under convolution ...

foreign direct investment has been a key topic in development literature for a long time. many economists have written articles on the on recipient’s macroeconomic variables, transfer of capital and technology. the improvement of managerial and human resources, promotion of foreign trade with its emphasized role on economic growth of recipients. other economists have an opposite view. they have...

in an effort to expand the disciplinary discussions on transfer in l2 writing and because most studies have focused on transfer as reuse and not as an adequate adaptation of writing knowledge in new contexts, the present study as the first of its kind aimed to explore the issue of adaptive transfer in an english for general academic purposes (egap) writing course. the study thus focused on type...

We examined the potential vulnerabilities of pilots flying a mixed fleet of two different aircraft types. A “worst case” scenario was evaluated in which a pilot, flying one type exclusively, would need to fly the different type, after 6 months without any recurrency training on the latter. These circumstances invite negative transfer of habits in the “old” aircraft, to performance in the “new” ...

Associative transfer was explored in the A-B, A-C and A-B, A-Br paradigms under three levels of stimulus similarity using an A-B, C-D control comparison. Three groups, differing in degree of structural similarity, learned two mixed lists of CVC trigrams by the anticipation method. A total of 90 sixth grade Ss were used. The effect of paradigms was highly siAnificant, with both the A-B, A-C and ...

In this paper we combine one method for hierarchical reinforcement learning—the options framework—with deep Q-networks (DQNs) through the use of different “option heads” on the policy network, and a supervisory network for choosing between the different options. We utilise our setup to investigate the effects of architectural constraints in subtasks with positive and negative transfer, across a...

We report on the mobilization of shuttle plasmids from gram-negative Escherichia coli to gram-positive corynebacteria mediated by P-type transfer functions. Introduction of plasmids into corynebacteria was markedly enhanced after heat treatment of the recipient cells. High-frequency plasmid transfer was also observed when the restriction system of the recipient was mutated. On the basis of our ...