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Microheater hotspot engineering for repeatable multi-level switching in foundry-processed phase change silicon photonics

Autor: Sun, Hongyi, Lian, Chuanyu, Vásquez-Aza, Francis, Kari, Sadra Rahimi, Huang, Yi-Siou, Restelli, Alessandro, Vitale, Steven A., Takeuchi, Ichiro, Hu, Juejun, Youngblood, Nathan, Pavlidis, Georges, Ocampo, Carlos A. Ríos

Nonvolatile photonic integrated circuits employing phase change materials have relied either on optical switching mechanisms with precise multi-level control but poor scalability or electrical switching with seamless integration and scalability but m

Externí odkaz: http://arxiv.org/abs/2407.00059

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Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management

Autor: Gupta, Dhawal, Chow, Yinlam, Tulepbergenov, Aza, Ghavamzadeh, Mohammad, Boutilier, Craig

Reinforcement learning (RL) has shown great promise for developing dialogue management (DM) agents that are non-myopic, conduct rich conversations, and maximize overall user satisfaction. Despite recent developments in RL and language models (LMs), u

Externí odkaz: http://arxiv.org/abs/2302.10850

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Akademický článek

Effects of bear endozoochory on germination and dispersal of huckleberry in the Canadian Rocky Mountains.

Autor: Kuijt, Aza Fynley¹ (AUTHOR) clayton.lamb@ubc.ca, Burton, Cole¹ (AUTHOR), Lamb, Clayton T.² (AUTHOR) fynley.kuijt@gmail.com

Publikováno v: PLoS ONE. 11/6/2024, Vol. 19 Issue 11, p1-15. 15p.

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Akademický článek

Bacteriological profile, antibiotic susceptibility, and biofilm formation in children with chronic suppurative otitis media

Autor: Taha, Aza Bahadeen ^⁎

Publikováno v: In International Journal of Pediatric Otorhinolaryngology January 2025 188

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Akademický článek

Information technology and online resources in the professional activities of preschool teachers

Autor: Batrakova, Irina, Ushanov, Alexander, Ioseliani, Aza

Publikováno v: Journal of Applied Research in Higher Education, 2021, Vol. 16, Issue 2, pp. 675-689.

Externí odkaz: http://www.emeraldinsight.com/doi/10.1108/JARHE-08-2021-0310

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A Mixture-of-Expert Approach to RL-based Dialogue Management

Autor: Chow, Yinlam, Tulepbergenov, Aza, Nachum, Ofir, Ryu, MoonKyung, Ghavamzadeh, Mohammad, Boutilier, Craig

Despite recent advancements in language models (LMs), their application to dialogue management (DM) problems and ability to carry on rich conversations remain a challenge. We use reinforcement learning (RL) to develop a dialogue agent that avoids bei

Externí odkaz: http://arxiv.org/abs/2206.00059

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