28th Annual Conference on Learning Theory (COLT), Paris 2015
Learning Theory is a research field devoted to studying the design and analysis of machine learning algorithms. In particular, such algorithms aim at making accurate predictions or representations based on observations.
The emphasis in COLT is on rigorous mathematical analysis using techniques from various connected fields such as probability, statistics, optimization, information theory and geometry. While theoretically rooted, learning theory puts a strong emphasis on efficient computation as well.
For more information visit the COLT 2015 website.
On-Line Learning & Bandits I
Optimization, Online Learning, Loss Functions
Estimation, Generative Models
On-Line Learning & Bandits II
Open Problems Session
Probabilistic Models and Reinforcement Learning