[R] Finding Errors in Perception Data With Learned Observation Assertions

ML models are increasingly being deployed in mission-critical settings, such as autonomous vehicles, but shockingly the data used to train these models are rarely checked! For example, the Lyft Level 5 dataset has errors in 70% of the validation scenes (see the images). Bad data can lead to bad models! Related work shows that bad data can effectively reduce model capacity by 3x (Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks)! See our blog post for more details: …

data errors machinelearning perception