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cs.LG2023
Semi-Supervised Learning with Multiple Imputations on Non-Random Missing Labels
Jason Lu, Michael Ma, Huaze Xu +1
Semi-Supervised Learning (SSL) is implemented when algorithms are trained on both labeled and unlabeled data. This is a very common application of ML as it is unrealistic to obtain…
cs.LG2023★ 2 cited
When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment
Tianwei Ni, Michel Ma, Benjamin Eysenbach +1
Reinforcement learning (RL) algorithms face two distinct challenges: learning effective representations of past and present observations, and determining how actions influence futu…