2021 Schedule:

• 11/23, Dr. Jack Han, Machine Learning: Principle, Evolution and Algorithms , [slides], [video] (needs CSUDH access).


• 8/11, Jennifer Ly, Multi-Agent Systems on Sensor Networks: A Distributed Reinforcement Learning Approach, [paper], [slides].


• 8/4, Phillip Aguilera, Mix-flow scheduling using deep reinforcement learning forsoftware-defined data-center networks , [paper].


• 7/28, Rachel Varghese, Reinforcement Learning to Play an Optimal Nash Equilibrium In Teach Markov Games, [paper].


• 7/28, Jennifer Ly, Raven: Scheduling Virtual Machine Migration during Data Center Updates with Reinforcement Learning, [paper], [slides].


• 7/21, Howard Luu, Multi-Agent Systems on Sensor Networks: A Distributed Reinforcement Learning Approach, [paper], [slides].


• 7/14, Lynn Gao, Ant-Q: A Reinforcement Learning approach tothe traveling salesman problem, [paper], [slides].


• 7/8, Multi-Agent Reinforcement Learning for Urban Crowd Sensing with For-Hire Vehicles, [paper].
  
  Asynchronous Deep Reinforcement Learning for Data-Driven Task Offloading in MEC-Empowered Vehicular Networks, [paper].


• 6/24, DeepReserve: Dynamic Edge Server Reservation for Connected Vehicles with Deep Reinforcement Learning, [paper].