Sentence examples for learning simultaneously from inspiring English sources

Sparse representation, on the other hand, finds a subset of elements from a dictionary and the corresponding weights to reconstruct an entire patch (dictionary learning simultaneously finds a dictionary).

Together, this shows that the effects in the first experiment of learning simultaneously paired associations are due to genuine cross-modal  facilitation.

Subjecting Fmr1 KO mice to treatment with Fenobam while performing locomotion conditioning tasks showed that the Erasmus Ladder can be used to test different types of learning simultaneously and to assess the impact of different drugs at a medium to high throughput level.

The proposed SOWC has the advantages of structure learning and parameter learning simultaneously.

This strategy makes the model jointly exploit the advantages of the CNN features with more structural information to effectively represent the target, and of both sparse representation and the incremental subspace learning simultaneously.

We showed that bees trained in a double discrimination task (one odorant rewarded with sucrose solutions vs. a different odorant punished with electric shock) learn to master both appetitive and aversive olfactory learning simultaneously, so that they exhibit the appropriate response, PER or SER, to the appropriate odorant.

Contestants were judged on a repertory that included three pas de deux that were not announced in advance but that everyone had to learn simultaneously.

This means that when the show begins, we learn simultaneously of Aeneas' arrival in Carthage by tempest-tossed seas (described in song by the vengeful goddess Juno, played by Kamala Sankaram) and the crash landing on the planet Aura by spaceships (with images from Mr. Bava's movie on monitors).

In task-driven formulation, the multi-modal dictionaries are learned simultaneously with their corresponding classifiers.

This approach learns simultaneously the geometry of the states and their connections.

The final classifier and the kernel function are learned simultaneously which has the advantage of using labeled data during the kernel learning process.