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20182023
most citedFederated Meta-Learning with Fast Convergence and Efficient Communication

270 citations · 491 across the 35 of their papers we have counts for

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5 papers · 1 filter

cs.LG2023★ 5 cited

Optimal Transport for Treatment Effect Estimation

Hao Wang, Zhichao Chen, Jiajun Fan +7

Estimating conditional average treatment effect from observational data is highly challenging due to the existence of treatment selection bias. Prevalent methods mitigate this issu…

cs.LG2023

Fair-CDA: Continuous and Directional Augmentation for Group Fairness

Rui Sun, Fengwei Zhou, Zhenhua Dong +6

In this work, we propose {\it Fair-CDA}, a fine-grained data augmentation strategy for imposing fairness constraints. We use a feature disentanglement method to extract the feature…

cs.LG2022

A Generalized Doubly Robust Learning Framework for Debiasing Post-Click Conversion Rate Prediction

Quanyu Dai, Haoxuan Li, Peng Wu +5

Post-click conversion rate (CVR) prediction is an essential task for discovering user interests and increasing platform revenues in a range of industrial applications. One of the m…

cs.LG2019★ 3 cited

Less Is Better: Unweighted Data Subsampling via Influence Function

Zifeng Wang, Hong Zhu, Zhenhua Dong +2

In the time of Big Data, training complex models on large-scale data sets is challenging, making it appealing to reduce data volume for saving computation resources by subsampling.…

cs.LG2018★ 270 cited

Federated Meta-Learning with Fast Convergence and Efficient Communication

Fei Chen, Mi Luo, Zhenhua Dong +2

Statistical and systematic challenges in collaboratively training machine learning models across distributed networks of mobile devices have been the bottlenecks in the real-world…