9 citations · 9 across the 4 of their papers we have counts for
4 papers · 1 filter
Heavy-Tailed Flow Matching via Random Clocks
Zhouhao Yang, Yezhen Wang, Kenji Kawaguchi +2
Heavy-tailed data arise in many domains where rare events carry disproportionate importance, such as imbalanced image datasets, financial returns, and weather extremes. Standard di…
Memory-Efficient LLM Training by Various-Grained Low-Rank Projection of Gradients
Yezhen Wang, Zhouhao Yang, Brian K Chen +4
Building upon the success of low-rank adapter (LoRA), low-rank gradient projection (LoRP) has emerged as a promising solution for memory-efficient fine-tuning. However, existing Lo…
Memory-Efficient Gradient Unrolling for Large-Scale Bi-level Optimization
Qianli Shen, Yezhen Wang, Zhouhao Yang +6
Bi-level optimization (BO) has become a fundamental mathematical framework for addressing hierarchical machine learning problems. As deep learning models continue to grow in size,…
Bias-Variance Trade-off in Physics-Informed Neural Networks with Randomized Smoothing for High-Dimensional PDEs
Zheyuan Hu, Zhouhao Yang, Yezhen Wang +2
While physics-informed neural networks (PINNs) have been proven effective for low-dimensional partial differential equations (PDEs), the computational cost remains a hurdle in high…