Sentence examples for performance of a target from inspiring English sources

The goal for transfer learning is to enhance the performance of a target task using an auxiliary/source domain.

Finally, simulation of the TCPN model allows to estimate performance of a target system implementation and to predict its behavior in various cases.

Domain adaptation, as it pertains to transfer learning, is the process of adapting one or more source domains for the means of transferring information to improve the performance of a target learner.

In this case, the goal of such task is to enhance the performance of a target text classification task which contains only unlabeled instances utilizing knowledge from a source domain with amble labeled and unlabeled documents.

To compare the performance of a targeted maximum likelihood estimator (TMLE) and a collaborative TMLE (CTMLE) to other estimators in a drug safety analysis, including a regression-based estimator, propensity score (PS based estimators, and an alternate doubly robust (DR) estimator in a real example and simulations.

This equipment would allow athletes to selectively engage with a landscape of performance-enhancing affordances and explore their athletic movement capacities, shared with performance behaviours of a target sport [36, 37].

The neutronic performance of a solid target system was compared with that of mercury target based on Monte Carlo calculations by using the MCNP code.

Factors influencing the I production are the thermal performance of target, the target composition, and the iodine separation.

Together with the extended high-gain observer, dynamic inversion results in performance recovery of a target system.

This system offers robust tracking performance of a moving target in several scenarios, such as rotational variation of input faces.

There are scenarios where a large amount of unlabeled heterogeneous source data is readily available that could be used to improve the predictive performance of a particular target learner.