Web: http://arxiv.org/abs/2201.12163

Jan. 31, 2022, 2:11 a.m. | Hiroshi Kajino, Kohei Miyaguchi, Takayuki Osogami

cs.LG updates on arXiv.org arxiv.org

We are interested in in silico evaluation methodology for molecular
optimization methods. Given a sample of molecules and their properties of our
interest, we wish not only to train an agent that can find molecules optimized
with respect to the target property but also to evaluate its performance. A
common practice is to train a predictor of the target property on the sample
and use it for both training and evaluating the agent. We show that this
evaluator potentially suffers …

arxiv bias biases evaluation optimization

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

Data Architect – Public Sector Health Data Architect, WWPS

@ Amazon.com | US, VA, Virtual Location - Virginia

[Job 8224] Data Engineer - Developer Senior

@ CI&T | Brazil

Software Engineer, Machine Learning, Planner/Behavior Prediction

@ Nuro, Inc. | Mountain View, California (HQ)

Lead Data Scientist

@ Inspectorio | Ho Chi Minh City, Ho Chi Minh City, Vietnam - Remote

Data Engineer

@ Craftable | Portugal - Remote

Sr. Data Scientist, Ads Marketplace Analytics

@ Reddit | Remote - United States