Difference between revisions of "ICTAI 2020"
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{{Event | {{Event | ||
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|Field=Artificial intelligence | |Field=Artificial intelligence | ||
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|Submission deadline=2020/06/10 | |Submission deadline=2020/06/10 | ||
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|Paper deadline=2020/06/10 | |Paper deadline=2020/06/10 | ||
|Notification=2020/08/16 | |Notification=2020/08/16 | ||
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|has program chair=Shimei Pan | |has program chair=Shimei Pan | ||
|Registration link=http://ictai2020.org/registration.html | |Registration link=http://ictai2020.org/registration.html | ||
| + | |Acronym=ICTAI 2020 | ||
| + | |End date=2020-11-11 | ||
| + | |Series=ICTAI | ||
| + | |Type =Conference | ||
| + | |Country=US | ||
| + | |State=US/MD | ||
| + | |City =US/MD/Baltimore | ||
| + | |Year =2020 | ||
| + | |Homepage=http://ictai2020.org/index.html | ||
| + | |Start date=2020-11-09 | ||
| + | |Title=32nd International Conference on Tools with Artificial Intelligence | ||
}} | }} | ||
==Topics== | ==Topics== | ||
Latest revision as of 04:39, 6 December 2021
Event Rating
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List of all ratings can be found at ICTAI 2020/rating
| ICTAI 2020 | |
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32nd International Conference on Tools with Artificial Intelligence
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| Event in series | ICTAI |
| Dates | 2020-11-09 (iCal) - 2020-11-11 |
| Homepage: | http://ictai2020.org/index.html |
| Submitting link: | http://ictai2020.org/submission.html |
| Location | |
| Location: | US/MD/Baltimore, US/MD, US |
| Important dates | |
| Papers: | 2020/06/10 |
| Submissions: | 2020/06/10 |
| Notification: | 2020/08/16 |
| Camera ready due: | 2020/09/20 |
| Registration link: | http://ictai2020.org/registration.html |
| Committees | |
| General chairs: | Miltos Alamaniotis |
| PC chairs: | Shimei Pan |
| Table of Contents | |
Topics
AI Foundations
- Machine Learning and Data Mining
- Evolutionary computing, Bayesian and Neural Networks
- Pre-processing, Dimension Reduction and Feature Selection
- Decision/Utility Theory and Decision Optimization
- Learning Graphical Models and Complex Networks
- Search, SAT, and CSP Active, Cost-Sensitive, Semi-Supervised, Multi-Instance, Multi-Label and Multi-Task Learning
- Description Logic and Ontologies
- Transfer/Adaptive, Rational and Structured Learning
AI in Domain-specific Applications
- Preference/Ranking, Ensemble, and Reinforcement Learning
AI in Computational Biology, Medicine and Biomedical Applications
- Knowledge Representation, Reasoning and Cognitive Modelling