The Conference for Machine Learning Innovation

Integrated Reinforcement learning and imitation learning using deep transfer learning Workshop

Workshop
Join the ML Revolution!
Register until August 12:
✓ML Intro Day for free
✓Save up to $380
Register Now
Join the ML Revolution!
Register until August 12:
✓ML Intro Day for free
✓Save up to $380
Register Now
Join the ML Revolution!
Register until August 19:
✓ML Intro Day for free
✓Save up to €490
Register Now
Join the ML Revolution!
Register until August 19:
✓ML Intro Day for free
✓Save up to €490
Register Now
Join the ML Revolution!
Register until the conference starts:
✓ 2-in-1 conference special
✓ 10 % Team Discount
Register Now
Join the ML Revolution!
Register until the conference starts:
✓ 2-in-1 conference special
✓ 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 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 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 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 Singapore Singapore , Berlin Berlin or oder Munich Munich .

Behind the Tracks