82 citations · 112 across the 6 of their papers we have counts for
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cs.CV2022
Learning from Training Dynamics: Identifying Mislabeled Data Beyond Manually Designed Features
Qingrui Jia, Xuhong Li, Lei Yu +5
While mislabeled or ambiguously-labeled samples in the training set could negatively affect the performance of deep models, diagnosing the dataset and identifying mislabeled sample…
cs.LG2022★ 1 cited
Backpropagation through Time and Space: Learning Numerical Methods with Multi-Agent Reinforcement Learning
Elliot Way, Dheeraj S. K. Kapilavai, Yiwei Fu +1
We introduce Backpropagation Through Time and Space (BPTTS), a method for training a recurrent spatio-temporal neural network, that is used in a homogeneous multi-agent reinforceme…