5 papers
Higher-order exponential Runge-Kutta Galerkin finite element method for semilinear parabolic problems with nonsmooth data
Shuo Yang, Runjie Zhang, Zhe Yu +1
We develop a rigorous numerical analysis framework for a class of semilinear parabolic problems with nonsmooth initial data. We employ a linear Galerkin finite element method for s…
Accumulative SGD Influence Estimation for Data Attribution
Yunxiao Shi, Shuo Yang, Yixin Su +2
Modern data-centric AI needs precise per-sample influence. Standard SGD-IE approximates leave-one-out effects by summing per-epoch surrogates and ignores cross-epoch compounding, w…
MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models
Yunxiao Shi, Shuo Yang, Haimin Zhang +4
Neural Collaborative Filtering models are widely used in recommender systems but are typically trained under static settings, assuming fixed data distributions. This limits their a…
GNSP: Gradient Null Space Projection for Preserving Cross-Modal Alignment in VLMs Continual Learning
Tiantian Peng, Yuyang Liu, Shuo Yang +2
Contrastive Language-Image Pretraining has demonstrated remarkable zero-shot generalization by aligning visual and textual modalities in a shared embedding space. However, when con…
Exponential Runge-Kutta Galerkin finite element method for a reaction-diffusion system with nonsmooth initial data
Runjie Zhang, Shuo Yang, Jinwei Fang
This study presents a numerical analysis of the Field-Noyes reaction-diffusion model with nonsmooth initial data, employing a linear Galerkin finite element method for spatial disc…