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|Title=30th International Conference on Algorithmic Learning Theory | |Title=30th International Conference on Algorithmic Learning Theory | ||
|Type=Conference | |Type=Conference | ||
| − | | | + | |Official Website=http://alt2019.algorithmiclearningtheory.org/ |
|City=Chicago | |City=Chicago | ||
|Country=Country:US | |Country=Country:US | ||
Revision as of 13:00, 19 October 2022
Deadlines
Metrics
Submitted Papers
78
Accepted Papers
37
Venue
Chicago, United States of America
Warning: Venue is missing. The map might not show the exact location.
Topics
- Design and analysis of learning algorithms.
- Statistical and computational learning theory.
- Online learning algorithms and theory.
- Optimization methods for learning.
- Unsupervised, semi-supervised, online and active learning.
- Connections of learning with other mathematical fields.
- Artificial neural networks, including deep learning.
- High-dimensional and non-parametric statistics.
- Learning with algebraic or combinatorial structure.
- Bayesian methods in learning.
- Planning and control, including reinforcement learning.
- Learning with system constraints: e.g. privacy, memory or communication budget.
- Learning from complex data: e.g., networks, time series, etc.
- Interactions with statistical physics.
- Learning in other settings: e.g. social, economic, and game-theoretic.
