Difference between revisions of "ICTAI 2020"
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==Topics== | ==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 |
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| − | + | === 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 |
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Revision as of 13:11, 26 March 2020
| ICTAI 2020 | |
|---|---|
32nd International Conference on Toools with Artificial Intelligence
| |
| 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: | Baltimore, Maryland, USA |
| 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: | Prof. Miltos Alamaniotis |
| PC chairs: | Prof. 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