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|Acronym=ICTAI 2020 | |Acronym=ICTAI 2020 | ||
|Title=32nd International Conference on Tools with Artificial Intelligence | |Title=32nd International Conference on Tools with Artificial Intelligence | ||
− | | | + | |In Event Series=Event Series:ICTAI |
− | | | + | |Single Day Event=no |
− | | | + | |Start Date=2020/11/09 |
+ | |End Date=2020/11/11 | ||
+ | |Event Status=as scheduled | ||
+ | |Event Mode=on site | ||
|City=Baltimore | |City=Baltimore | ||
|Region=Maryland | |Region=Maryland | ||
|Country=Country:US | |Country=Country:US | ||
− | | | + | |Academic Field=Artificial Intelligence |
− | | | + | |Official Website=http://ictai2020.org/index.html |
− | | | + | |Submission Link=http://ictai2020.org/submission.html |
− | | | + | |Registration Link=http://ictai2020.org/registration.html |
− | | | + | |DOI=10.25798/3gvs-w174 |
+ | |Type=Conference | ||
|has general chair=Miltos Alamaniotis | |has general chair=Miltos Alamaniotis | ||
|has program chair=Shimei Pan | |has program chair=Shimei Pan | ||
− | |||
|pageCreator=User:Curator 39 | |pageCreator=User:Curator 39 | ||
|pageEditor=User:Curator 89 | |pageEditor=User:Curator 89 | ||
|contributionType=1 | |contributionType=1 | ||
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}} | }} | ||
+ | {{Event Deadline | ||
+ | |Notification Deadline=2020/08/16 | ||
+ | |Paper Deadline=2020/06/10 | ||
+ | |Camera-Ready Deadline=2020/09/20 | ||
+ | |Submission Deadline=2020/06/10 | ||
+ | }} | ||
+ | {{Organizer | ||
+ | |Contributor Type=organization | ||
+ | |Organization=IEEE | ||
+ | }} | ||
+ | {{Event Metric}} | ||
+ | {{S Event}} | ||
==Topics== | ==Topics== | ||
− | === AI Foundations === | + | ===AI Foundations=== |
− | * Machine Learning and Data Mining | + | *Machine Learning and Data Mining |
− | * Evolutionary computing, Bayesian and Neural Networks | + | *Evolutionary computing, Bayesian and Neural Networks |
− | * Pre-processing, Dimension Reduction and Feature Selection | + | *Pre-processing, Dimension Reduction and Feature Selection |
− | * Decision/Utility Theory and Decision Optimization | + | *Decision/Utility Theory and Decision Optimization |
− | * Learning Graphical Models and Complex Networks | + | *Learning Graphical Models and Complex Networks |
− | * Search, SAT, and CSP Active, Cost-Sensitive, Semi-Supervised, Multi-Instance, Multi-Label and Multi-Task Learning | + | *Search, SAT, and CSP Active, Cost-Sensitive, Semi-Supervised, Multi-Instance, Multi-Label and Multi-Task Learning |
− | * Description Logic and Ontologies | + | *Description Logic and Ontologies |
− | * Transfer/Adaptive, Rational and Structured Learning | + | *Transfer/Adaptive, Rational and Structured Learning |
− | === AI in Domain-specific Applications === | + | ===AI in Domain-specific Applications=== |
− | * Preference/Ranking, Ensemble, and Reinforcement Learning | + | *Preference/Ranking, Ensemble, and Reinforcement Learning |
− | === AI in Computational Biology, Medicine and Biomedical Applications | + | ===AI in Computational Biology, Medicine and Biomedical Applications=== |
− | * Knowledge Representation, Reasoning and Cognitive Modelling | + | *Knowledge Representation, Reasoning and Cognitive Modelling |
Latest revision as of 09:30, 7 July 2023
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Venue
Baltimore, Maryland, United States of America
Warning: Venue is missing. The map might not show the exact location.
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