13 citations · 41 across the 10 of their papers we have counts for
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cs.LG2023★ 8 cited
MLCopilot: Unleashing the Power of Large Language Models in Solving Machine Learning Tasks
Lei Zhang, Yuge Zhang, Kan Ren +2
The field of machine learning (ML) has gained widespread adoption, leading to significant demand for adapting ML to specific scenarios, which is yet expensive and non-trivial. The…
cs.LG2023
Towards Inference Efficient Deep Ensemble Learning
Ziyue Li, Kan Ren, Yifan Yang +3
Ensemble methods can deliver surprising performance gains but also bring significantly higher computational costs, e.g., can be up to 2048X in large-scale ensemble tasks. However,…
cs.LG2022★ 4 cited
Reinforcement Learning with Automated Auxiliary Loss Search
Tairan He, Yuge Zhang, Kan Ren +5
A good state representation is crucial to solving complicated reinforcement learning (RL) challenges. Many recent works focus on designing auxiliary losses for learning informative…