Zobrazeno 1 - 10
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pro vyhledávání: '"HARRIS, Justin"'
Autor:
Leeming, Paul, Harris, Justin
Publikováno v:
In Research Methods in Applied Linguistics April 2024 3(1)
Autor:
Harris, Justin D.
Machine learning has recently enabled large advances in artificial intelligence, but these results can be highly centralized. The large datasets required are generally proprietary; predictions are often sold on a per-query basis; and published models
Externí odkaz:
http://arxiv.org/abs/2009.06756
Publikováno v:
Comput. Brain Behav. (2021)
We check the robustness of a recently proposed dynamical model of associative Pavlovian learning that extends the Rescorla-Wagner (RW) model in a natural way and predicts progressively damped oscillations in the response of the subjects. Using the da
Externí odkaz:
http://arxiv.org/abs/2004.05069
In this paper, we propose a method for incorporating world knowledge (linked entities and fine-grained entity types) into a neural question generation model. This world knowledge helps to encode additional information related to the entities present
Externí odkaz:
http://arxiv.org/abs/1909.03716
Autor:
Harris, Justin D., Waggoner, Bo
Machine learning has recently enabled large advances in artificial intelligence, but these tend to be highly centralized. The large datasets required are generally proprietary; predictions are often sold on a per-query basis; and published models can
Externí odkaz:
http://arxiv.org/abs/1907.07247
Autor:
Loomes, Max, Tran, Dominic M.D., Chowdhury, Nahian S., Birney, Damian P., Harris, Justin A., Livesey, Evan J.
Publikováno v:
In Cortex March 2023 160:100-114
Akademický článek
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Akademický článek
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Autor:
Tang, Wenyue, Wu, Pingkeng, Da, Chang, Alzobaidi, Shehab, Harris, Justin, Hallaman, Brooke, Hu, Dongdong, Johnston, Keith P.
Publikováno v:
In Fuel 1 January 2023 331 Part 2
Autor:
Asri, Layla El, Schulz, Hannes, Sharma, Shikhar, Zumer, Jeremie, Harris, Justin, Fine, Emery, Mehrotra, Rahul, Suleman, Kaheer
This paper presents the Frames dataset (Frames is available at http://datasets.maluuba.com/Frames), a corpus of 1369 human-human dialogues with an average of 15 turns per dialogue. We developed this dataset to study the role of memory in goal-oriente
Externí odkaz:
http://arxiv.org/abs/1704.00057