73 citations · 142 across the 31 of their papers we have counts for
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cs.LG2024
Score-based Conditional Out-of-Distribution Augmentation for Graph Covariate Shift
Bohan Wang, Yurui Chang, Wei Jin +1
Distribution shifts between training and testing datasets significantly impair the model performance on graph learning. A commonly-taken causal view in graph invariant learning sug…
cs.LG2024
On the Convergence of Adam under Non-uniform Smoothness: Separability from SGDM and Beyond
Bohan Wang, Huishuai Zhang, Qi Meng +3
This paper aims to clearly distinguish between Stochastic Gradient Descent with Momentum (SGDM) and Adam in terms of their convergence rates. We demonstrate that Adam achieves a fa…
cs.LG2024
Continuous-time Riemannian SGD and SVRG Flows on Wasserstein Probabilistic Space
Mingyang Yi, Bohan Wang
Recently, optimization on the Riemannian manifold have provided valuable insights to the optimization community. In this regard, extending these methods to to the Wasserstein space…