3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2023
Invariant-Feature Subspace Recovery: A New Class of Provable Domain Generalization Algorithms
Haoxiang Wang, Gargi Balasubramaniam, Haozhe Si +2
Domain generalization asks for models trained over a set of training environments to generalize well in unseen test environments. Recently, a series of algorithms such as Invariant…
cs.LG2023★ 3 cited
Federated Learning with Classifier Shift for Class Imbalance
Yunheng Shen, Haoxiang Wang, Hairong Lv
Federated learning aims to learn a global model collaboratively while the training data belongs to different clients and is not allowed to be exchanged. However, the statistical he…
cs.LG2022
Future Gradient Descent for Adapting the Temporal Shifting Data Distribution in Online Recommendation Systems
Mao Ye, Ruichen Jiang, Haoxiang Wang +6
One of the key challenges of learning an online recommendation model is the temporal domain shift, which causes the mismatch between the training and testing data distribution and…