| Event | When | Where | Deadline |
| COLT 2021 |
Computational Learning Theory |
| Aug 15, 2021 - Aug 19, 2021 |
Boulder, Colorado |
Jan 29, 2021 |
| COLT 2020 |
Conference on Learning Theory (COLT) |
| Jul 9, 2020 - Jul 12, 2020 |
Graz, Austria |
Jan 31, 2020 |
| COLT 2019 |
Computational Learning Theory |
| Jun 25, 2019 - Jun 29, 2019 |
Phoenix, AZ, USA |
Feb 1, 2019 |
| COLT 2018 |
Computational Learning Theory |
| Jul 5, 2018 - Jul 9, 2018 |
Stockholm, Sweden |
Feb 16, 2018 |
| COLT 2017 |
Computational Learning Theory |
| Jul 7, 2017 - Jul 10, 2017 |
Amsterdam, Netherlands |
Feb 17, 2017 |
| COLT 2016 |
Conference on Learning Theory |
| Jun 23, 2016 - Jun 26, 2016 |
New York, NY, USA |
Feb 12, 2016 |
| COLT 2015 |
Conference on Learning Theory 2015 |
| Jul 3, 2015 - Jul 3, 2015 |
Paris, France |
Feb 19, 2015 |
| COLT 2014 |
Conference on Learning Theory |
| Jun 13, 2014 - Jun 15, 2014 |
Barcelona, Spain |
Feb 7, 2014 |
| COLT 2013 |
26th Annual Conference on Learning Theory |
| Jun 12, 2013 - Jun 14, 2013 |
Princeton, NJ, USA |
Feb 8, 2013 |
| COLT 2012 |
25th Annual Conference on Learning Theory |
| Jun 25, 2012 - Jun 27, 2012 |
Edinburgh, Scotland |
Feb 14, 2012 |
| COLT 2011 |
The 24rd Annual Conference on Learning Theory |
| Jul 9, 2011 - Jul 11, 2011 |
Budapest, Hungary |
Feb 11, 2011 |
| COLT 2010 |
The 23rd International Conference on Learning Theory |
| Jun 27, 2010 - Jun 29, 2010 |
Haifa, Israel |
Feb 19, 2010 |
| COLT 2009 |
The 22nd Annual Conference on Learning Theory |
| Jun 18, 2009 - Jun 21, 2009 |
Montreal, Canada |
Feb 13, 2009 |
| COLT 2008 |
Conference on Learning Theory |
| Jul 9, 2008 - Jul 12, 2008 |
Helsinki, Finland |
Feb 20, 2008 |
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The 34th Annual Conference on Learning Theory (COLT 2021) will take place August 15-19, 2021. Assuming the circumstances allow for an in-person conference it will be held at CU Boulder, in Colorado. We invite submissions of papers addressing theoretical aspects of machine learning, broadly defined as a subject at the intersection of computer science, statistics and applied mathematics. We strongly support an inclusive view of learning theory, including fundamental theoretical aspects of learnability in various contexts, and theory that sheds light on empirical phenomena.
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