Difference between revisions of "ICTAI 2020"
Jump to navigation
Jump to search
(modified through wikirestore by orapi) |
(modified through wikirestore by orapi) |
||
Line 20: | Line 20: | ||
|Homepage=http://ictai2020.org/index.html | |Homepage=http://ictai2020.org/index.html | ||
|Start date=2020-11-09 | |Start date=2020-11-09 | ||
− | |Title=32nd International Conference on Tools with Artificial Intelligence}} | + | |Title=32nd International Conference on Tools with Artificial Intelligence |
+ | }} | ||
==Topics== | ==Topics== | ||
=== AI Foundations === | === AI Foundations === |
Latest revision as of 04:39, 6 December 2021
Event Rating
median | worst |
---|---|
![]() |
![]() |
List of all ratings can be found at ICTAI 2020/rating
ICTAI 2020 | |
---|---|
32nd International Conference on Tools 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: | 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