Fengmiao Bian — accepted AI-conference papers

2025

Finding Low-Rank Matrix Weights in DNNs via Riemannian Optimization: RAdaGrad and RAdamW

Fengmiao Bian, Jinyang ZHENG, Ziyun Liu, Jianzhou Luo, Jian-Feng Cai

NeurIPS 2025poster

Finding low-rank matrix weights is a key technique for addressing the high memory usage and computational demands of large models. Most existing algorithms rely on the factorization of the low-rank matrix weights, which is non-unique and redundant. Their convergence is slow especially when the targe…

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2025

Preconditioned Riemannian Gradient Descent Algorithm for Low-Multilinear-Rank Tensor Completion

Yuanwei Zhang, Fengmiao Bian, Xiaoqun Zhang, Jian-Feng Cai

ICML 2025poster

Tensors play a crucial role in numerous scientific and engineering fields. This paper addresses the low-multilinear-rank tensor completion problem, a fundamental task in tensor-related applications. By exploiting the manifold structure inherent to the fixed-multilinear-rank tensor set, we introduce…

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