m (Text replacement - "=User:Curator 83" to "=Ch") |
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|Homepage=http://alt2019.algorithmiclearningtheory.org/ | |Homepage=http://alt2019.algorithmiclearningtheory.org/ | ||
|City=Chicago | |City=Chicago | ||
| − | |Country= | + | |Country=Country:US |
|Has coordinator=Lev Reyzin, Gyorgy Turan | |Has coordinator=Lev Reyzin, Gyorgy Turan | ||
|has program chair=Satyen Kale, Aurélien Garivier | |has program chair=Satyen Kale, Aurélien Garivier | ||
| Line 20: | Line 20: | ||
|Start Date=2019/03/22 | |Start Date=2019/03/22 | ||
|End Date=2019/03/24 | |End Date=2019/03/24 | ||
| + | |Event Status=as scheduled | ||
| + | |Event Mode=on site | ||
}} | }} | ||
== Topics == | == Topics == | ||
Revision as of 13:38, 6 September 2022
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.
