Web: http://arxiv.org/abs/2201.11182

Jan. 28, 2022, 2:10 a.m. | Mariam Kiran, Melis Ozyildirim

cs.LG updates on arXiv.org arxiv.org

Reinforcement learning (RL) applications, where an agent can simply learn
optimal behaviors by interacting with the environment, are quickly gaining
tremendous success in a wide variety of applications from controlling simple
pendulums to complex data centers. However, setting the right hyperparameters
can have a huge impact on the deployed solution performance and reliability in
the inference models, produced via RL, used for decision-making. Hyperparameter
search itself is a laborious process that requires many iterations and
computationally expensive to find the …

applications arxiv deep learning reinforcement learning

More from arxiv.org / cs.LG updates on arXiv.org

Machine Learning Product Manager (Europe, Remote)

@ FreshBooks | Germany

Field Operations and Data Engineer, ADAS

@ Lucid Motors | Newark, CA

Machine Learning Engineer - Senior

@ Novetta | Reston, VA

Analytics Engineer

@ ThirdLove | Remote

Senior Machine Learning Infrastructure Engineer - Safety

@ Discord | San Francisco, CA or Remote

Internship, Data Scientist

@ Everstream Analytics | United States (Remote)