46 citations · 156 across the 29 of their papers we have counts for
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stat.ML2022★ 3 cited
TuneUp: A Simple Improved Training Strategy for Graph Neural Networks
Weihua Hu, Kaidi Cao, Kexin Huang +4
Despite recent advances in Graph Neural Networks (GNNs), their training strategies remain largely under-explored. The conventional training strategy learns over all nodes in the or…
stat.ML2022★ 16 cited
Learning Backward Compatible Embeddings
Weihua Hu, Rajas Bansal, Kaidi Cao +3
Embeddings, low-dimensional vector representation of objects, are fundamental in building modern machine learning systems. In industrial settings, there is usually an embedding tea…
stat.ML2021★ 2 cited
Scalable Feature Selection for (Multitask) Gradient Boosted Trees
Cuize Han, Nikhil Rao, Daria Sorokina +1
Gradient Boosted Decision Trees (GBDTs) are widely used for building ranking and relevance models in search and recommendation. Considerations such as latency and interpretability…