Deep Reinforcement Learning Part 2 - Volodymyr Mnih - MLSS 2017 @mpi-is
Deep Reinforcement Learning Part 2 - Volodymyr Mnih - MLSS 2017 @mpi-is
Uploaded January 2018 | Updated September 2026, 1 hour ago
This is Volodymyr Mnih's second talk of his lecture series, given at the Machine Learning Summer School 2017, held at the Max Planck Institute for Intelligent Systems, in Tübingen, Germany, from 19-30 June 2017.

Slides for this talk, in pdf format, as well as an overview and links to other talks held during the Summer School, can be found at mlss.tuebingen.mpg.de/2017
Deep Reinforcement Learning Part 2 - Volodymyr Mnih - MLSS 2017Learning Digital Humans by Capturing Real Ones - Michael Black - MLSS 2017Multilayer Networks 3 - Léon Bottou - MLSS 2013 Tübingen2020 Intelligent Systems Summer Colloquium (Part 1)Graphical Models 2 - Christopher Bishop - MLSS 2013 TübingenStructured Output Prediction 1 - Thomas Hofmann - MLSS 2013 TübingenMultilayer Networks 1 - Léon Bottou - MLSS 2013 TübingenOptimization 2 - Stephen Wright - MLSS 2013 TübingenDistributed Architectures Part 1 - Michael Jordan - MLSS 2017Bayesian Nonparametrics 1 - Yee Whye Teh - MLSS 2013 TübingenMagnetic Microalgae on a mission to become robots10 Jahre MPI für Intelligente Systeme, 100 Jahre MPI für Metallforschung
Max Planck Institute for Intelligent Systems |

Deep Reinforcement Learning Part 2 - Volodymyr Mnih - MLSS 2017

SHARE TO X SHARE TO REDDIT SHARE TO FACEBOOK WALLPAPER