Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Nir Levine"'
Autor:
Daniel J. Mankowitz, Cosmin Paduraru, Gabriel Dulac-Arnold, Nir Levine, Jerry Li, Todd Hester, Sven Gowal
Publikováno v:
Machine Learning. 110:2419-2468
Reinforcement learning (RL) has proven its worth in a series of artificial domains, and is beginning to show some successes in real-world scenarios. However, much of the research advances in RL are hard to leverage in real-world systems due to a seri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::48400b369d20140e3d3fb921d47b7dd2
https://doi.org/10.1007/s10994-021-05961-4
https://doi.org/10.1007/s10994-021-05961-4
Autor:
Ang Li, Nir Levine, Mehrdad Farajtabar, Akihiro Matsukawa, Seyed Iman Mirzadeh, Hassan Ghasemzadeh
Publikováno v:
AAAI
Despite the fact that deep neural networks are powerful models and achieve appealing results on many tasks, they are too large to be deployed on edge devices like smartphones or embedded sensor nodes. There have been efforts to compress these network
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::168ef0afd7a4ecd169e4b1d36d755c3f
Publikováno v:
SIGIR
The session search task aims at best serving the user's information need given her previous search behavior during the session. We propose an extended relevance model that captures the user's dynamic information need in the session. Our relevance mod
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::68be104d8a2fb3655b3a814f3b495453
https://doi.org/10.1145/3077136.3080664
https://doi.org/10.1145/3077136.3080664