Using Recommender Systems to Improve Proactive Modeling (MODELS 2021 - Technical Papers) - MODELS 2021

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Sun 10 - Sat 16 October 2021

Who

James Hill, Arvind Nair, Xia Ning

Track

MODELS 2021 Technical Papers

Time Zone

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When

Wed 13 Oct 2021 09:00 - 09:20 at Room 1 - Machine learning and Recommender systems I Chair(s): Betty H.C. Cheng

James Hill

Arvind Nair

Xia Ning

Time Zone

The program is currently displayed in (GMT+09:00) Osaka, Sapporo, Tokyo.

Use conference time zone: (GMT+09:00) Osaka, Sapporo, TokyoSelect other time zone

The GMT offsets shown reflect the offsets at the moment of the conference.

Time Band

By setting a time band, the program will dim events that are outside this time window. This is useful for (virtual) conferences with a continuous program (with repeated sessions).
The time band will also limit the events that are included in the personal iCalendar subscription service.

Display full programSpecify a time band

Session Program

Wed 13 Oct
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	09:00 - 10:00	Machine learning and Recommender systems ITechnical Papers at Room 1 Chair(s): Betty H.C. Cheng Michigan State University

	09:00 20m Talk		Using Recommender Systems to Improve Proactive ModelingJ1ST Technical Papers James Hill , Arvind Nair , Xia Ning
	09:20 20m Talk		Predictions-on-Chip: Model-based Training and Automated Deployment of Machine Learning Models at RuntimeJ1ST Technical Papers Sebastian Pilarski McGill University, Martin Staniszewski , Matthew Bryan , Frederic Villeneuve , Daniel Varro McGill University / Budapest University of Technology and Economics
	09:40 10m Demonstration		DoMoBOT: An AI-Empowered Bot for Automated and Interactive Domain ModellingDEMO Technical Papers Rijul Saini McGill University, Canada, Gunter Mussbacher McGill University, Jin L.C. Guo McGill University, Jörg Kienzle McGill University, Canada