9.1 模型调参【stanford-cs329p】
KDD-2019 MeLU:Meta-Learned User Preference Estimator for Cold-Start Recommendation
ICML-2017 Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
5.4 Stacking【stanford-cs329p】
5.3 Boosting【stanford-cs329p】
ICSE-2021 InferCode:Self-Supervised Learning of Code Representations by Predicting Subtrees
ECCV-2020 End-to-End Object Detection with Transformers
5.2 Bagging【stanford-cs329p】
5.1 方差和偏差【stanford-cs329p】
ICPC-2022 HELoC:Hierarchical Contrastive Learning of Source Code Representation
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