62 citations · 176 across the 28 of their papers we have counts for
4 papers · 1 filter
Low-Shot Validation: Active Importance Sampling for Estimating Classifier Performance on Rare Categories
Fait Poms, Vishnu Sarukkai, Ravi Teja Mullapudi +4
For machine learning models trained with limited labeled training data, validation stands to become the main bottleneck to reducing overall annotation costs. We propose a statistic…
Video Pose Distillation for Few-Shot, Fine-Grained Sports Action Recognition
James Hong, Matthew Fisher, Michaël Gharbi +1
Human pose is a useful feature for fine-grained sports action understanding. However, pose estimators are often unreliable when run on sports video due to domain shift and factors…
Mandoline: Model Evaluation under Distribution Shift
Mayee Chen, Karan Goel, Nimit S. Sohoni +3
Machine learning models are often deployed in different settings than they were trained and validated on, posing a challenge to practitioners who wish to predict how well the deplo…
Large Batch Simulation for Deep Reinforcement Learning
Brennan Shacklett, Erik Wijmans, Aleksei Petrenko +4
We accelerate deep reinforcement learning-based training in visually complex 3D environments by two orders of magnitude over prior work, realizing end-to-end training speeds of ove…