The main aim of this conference is to bring together both national and international scientists and PhD students working in the 
 area of Theoretical Machine Learning in order to create an opportunity to exchange knowledge and current research directions.
 Scope of TFML consists of (but is not limited to): classification theory, clustering, ensemble models, generalization bounds (and
 related VC dimension), deep learning, information theory and entropy based methods, density estimation techniques,
 probabilistic and statistical foundations of machine learning.