View source for ALT 2019

{{Event
|Acronym=ALT 2019
|Title=30th International Conference on Algorithmic Learning Theory
|Series=ALT
|Type=Conference
|Start date=2019/03/22
|End date=2019/03/24
|Homepage=http://alt2019.algorithmiclearningtheory.org/
|City=Chicago
|Country=USA
|Has coordinator=Lev Reyzin, Gyorgy Turan
|has program chair=Satyen Kale, Aurélien Garivier
|has workshop chair=Steve Hanneke
|Has PC member=Naman Agarwal, Kareem Amin, Borja Balle, Achilles Beros, Gilles Blanchard, Sébastien Bubeck
|has Keynote speaker=Sanjeev Arora, Jennifer Wortman Vaughan
|Submitted papers=78
|Accepted papers=37
}}
== 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.