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cs.LG2025
Bridging the Divide: End-to-End Sequence-Graph Learning
Yuen Chen, Yulun Wu, Samuel Sharpe +5
Many real-world prediction tasks, particularly those involving entities such as customers or patients, involve both {sequential} and {relational} data. Each entity maintains its ow…
cs.LG2025
DIVEBATCH: Accelerating Model Training Through Gradient-Diversity Aware Batch Size Adaptation
Yuen Chen, Yian Wang, Hari Sundaram
The goal of this paper is to accelerate the training of machine learning models, a critical challenge since the training of large-scale deep neural models can be computationally ex…
cs.LG2025
Moment Alignment: Unifying Gradient and Hessian Matching for Domain Generalization
Yuen Chen, Haozhe Si, Guojun Zhang +1
Domain generalization (DG) seeks to develop models that generalize well to unseen target domains, addressing the prevalent issue of distribution shifts in real-world applications.…