Asymptotics and Non-Asymptotics in Control and RL
Asymptotics and Non-Asymptotics in Control and RL
Reinforcement learning is a highly active area of research, blending ideas and techniques from control, optimization, machine learning, and computer science. Given this diversity of viewpoints and frameworks, it is imperative to understand their strengths and their limitations. The aim of this iDS2 virtual mini-workshop is a constructive dialogue and exchange of ideas between researchers in these fields. It will feature two tutorial-style talks emphasizing the asymptotic and the non-asymptotic perspectives, followed by a moderated discussion featuring the speakers.
All events in this mini-workshop will be take place on
Fridays, April 16, April 23, April 30
from 12:30 pm to 3:00 pm CST, with a break from 1:30 pm to 2:00 pm
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From Maxim Raginsky
85 plays 0Zoom Recording ID: 87261780923 UUID: 8HRErWlfQ/i7ODduT15Q3A== Meeting Time: 2021-04-30T17:27:22Z -
From Maxim Raginsky
254 plays 0iDS^2 Mini-Workshop on Asymptotics and Non-Asymptotics in Control and Reinforcement Learning -
From Maxim Raginsky
320 plays 0iDS^2 Mini-Workshop on Asymptotics and Non-Asymptotics in Control and Reinforcement Learning