Web: http://arxiv.org/abs/2201.03916

Jan. 12, 2022, 2:10 a.m. | Jack Parker-Holder, Raghu Rajan, Xingyou Song, André Biedenkapp, Yingjie Miao, Theresa Eimer, Baohe Zhang, Vu Nguyen, Roberto Calandra, Aleksandr

cs.LG updates on arXiv.org arxiv.org

The combination of Reinforcement Learning (RL) with deep learning has led to
a series of impressive feats, with many believing (deep) RL provides a path
towards generally capable agents. However, the success of RL agents is often
highly sensitive to design choices in the training process, which may require
tedious and error-prone manual tuning. This makes it challenging to use RL for
new problems, while also limits its full potential. In many other areas of
machine learning, AutoML has shown it is possible to automate such design
choices and has …

arxiv learning open reinforcement learning survey

Statistics and Computer Science Specialist

@ Hawk-Research | Remote

Data Scientist, Credit/Fraud Strategy

@ Fora Financial | New York City

Postdoctoral Research Associate - Biomedical Natural Language Processing and Deep Learning

@ Oak Ridge National Laboratory - Oak Ridge, TN | Oak Ridge, TN, United States

Senior Machine Learning / Computer Vision Engineer

@ Glass Imaging | Los Altos, CA

Research Scientist in Biomedical Natural Language Processing and Deep Learning

@ Oak Ridge National Laboratory | Oak Ridge, TN

W3-Professorship for Intelligent Energy Management

@ Universität Bayreuth | Bayreuth, Germany