Difference between revisions of "ADMI 2017"
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{{Event | {{Event | ||
| + | |Acronym=ADMI 2017 | ||
| + | |Title=13th International Workshop on Agents and Data Mining Interaction | ||
| + | |Series=ADMI | ||
| + | |Type=Conference | ||
| + | |Start date=2017/05/08 | ||
| + | |End date=2017/05/08 | ||
|Submission deadline=2017/02/05 | |Submission deadline=2017/02/05 | ||
| + | |Homepage=http://admi17.agentmining.org/ | ||
| + | |City=São Paulo | ||
| + | |Country=Brazil | ||
|has general chair=Philip S. Yu, Longbing Cao | |has general chair=Philip S. Yu, Longbing Cao | ||
|has program chair=Yifeng Zeng, Yang Gao, Hao Wang, Yingke Chen | |has program chair=Yifeng Zeng, Yang Gao, Hao Wang, Yingke Chen | ||
| − | + | |State=BR/SP}} | |
| − | |||
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| − | |State | ||
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The Thirteenth International Workshop on Agents and Data Mining Interaction (ADMI-17), Sao Paulo, Brazil, May 8, 2017 | The Thirteenth International Workshop on Agents and Data Mining Interaction (ADMI-17), Sao Paulo, Brazil, May 8, 2017 | ||
http://admi17.agentmining.org/ | http://admi17.agentmining.org/ | ||
Revision as of 22:43, 24 October 2021
Event Rating
| median | worst |
|---|---|
List of all ratings can be found at ADMI 2017/rating
| ADMI 2017 | |
|---|---|
13th International Workshop on Agents and Data Mining Interaction
| |
| Event in series | ADMI |
| Dates | 2017/05/08 (iCal) - 2017/05/08 |
| Homepage: | http://admi17.agentmining.org/ |
| Location | |
| Location: | São Paulo, BR/SP, Brazil |
| Important dates | |
| Submissions: | 2017/02/05 |
| Committees | |
| General chairs: | Philip S. Yu, Longbing Cao |
| PC chairs: | Yifeng Zeng, Yang Gao, Hao Wang, Yingke Chen |
| Table of Contents | |
The Thirteenth International Workshop on Agents and Data Mining Interaction (ADMI-17), Sao Paulo, Brazil, May 8, 2017 http://admi17.agentmining.org/
Held in conjunction with Sixteenth International Joint Conference on AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS (AAMAS-2017) http://www.aamas2017.org/
Topics
- Data-driven decision making and planning
- Data-driven reasoning and learning
- Data-driven agent interaction and coordination
- Data-driven personalized agents
- Deep learning for agent systems
- Agent-based methods and tools for big data analysis
- Applications of data-driven agent systems