The Conference for Machine Learning Innovation

Integrated Reinforcement learning and imitation learning using deep transfer learning Workshop

Workshop
Join the ML Revolution!
Register until April15:
✓Save up to 310 €
✓ 2-in-1 conference special
✓10 % Team Discount
Register Now
Join the ML Revolution!
Register until April15:
✓Save up to 310 €
✓ 2-in-1 conference special
✓10 % Team Discount
Register Now
Join the ML Revolution!
Register until December 12:
✓ML Intro Day for free
✓Raspberry Pi or C64 Mini for free
✓Save up to $580
Register Now
Join the ML Revolution!
Register until December 12:
✓ML Intro Day for free
✓Raspberry Pi or C64 Mini for free
✓Save up to $580
Register Now
Join the ML Revolution!
Register until November 7th:
✓Save up to € 210
✓10% Team Discount
Register Now
Join the ML Revolution!
Register until November 7th:
✓Save up to € 210
✓10% Team Discount
Register Now
Infos
Booking note:
Reinforcement Learning Workshop

Deep Reinforcement-Learning (RL) in various decision-making tasks of Machine-Learning (ML) provides effective results with an agent/agents learning from observing an environment and gaining rewards and punishments. RL as a great technique in ML shows its ability to be utilized in different time-series and Computer Vision-based (CV) projects like autonomous driving, robotics, traffic control, web system configuration, recommendation systems and game applications. In complex environments where RL underperforms as a consequence of extensive demonstration information in long-horizon problems, Imitation Learning (IL) offers a promising solution for the challenges. In IL, the learning process can take advantage of human-sourced assistance and/or control over the agent and environment. The purpose of this talk is to provide an introduction to Deep RL and IL at a level easily understood by students and researchers in a wide range of disciplines. Also, we will overview different RL and IL techniques and methods as long as discuss how they are utilized to improve the performance of different tasks. Also, we cover the usage of RL and IL in CV, NLP and time-series tasks.

This Session originates from the archive of Diese Session stammt aus dem Archiv von MunichMunich . Take me to the program of . Hier geht es zum aktuellen Programm von Munich Munich .

This Session originates from the archive of Diese Session stammt aus dem Archiv von MunichMunich . Take me to the program of . Hier geht es zum aktuellen Programm von Singapore Singapore .

This Session originates from the archive of Diese Session stammt aus dem Archiv von MunichMunich . Take me to the program of . Hier geht es zum aktuellen Programm von Berlin Berlin .

This Session Diese Session originates from the archive of stammt aus dem Archiv von MunichMunich . Take me to the current program of . Hier geht es zum aktuellen Programm von Munich Munich , Singapore Singapore or oder Berlin Berlin .

Behind the Tracks