23 citations · 24 across the 8 of their papers we have counts for
8 papers
FILO: A Unified Fisher-Geometric Framework for Low-Rank Adaptation
Ziyun Liu, Fengmiao Bian, Jian-Feng Cai
Low-Rank Adaptation (LoRA) reparameterizes a weight matrix as a product of two low-rank factors, but the Jacobian of the generator mapping the factors to the weight matri…
Fast and Provable Tensor-Train Format Tensor Completion via Precondtioned Riemannian Gradient Descent
Fengmiao Bian, Jian-Feng Cai, Xiaoqun Zhang +1
Low-rank tensor completion aims to recover a tensor from partially observed entries, and it is widely applicable in fields such as quantum computing and image processing. Due to th…
Stochastic Three-Operator Splitting Algorithms for Nonconvex and Nonsmooth Optimization Arising from FLASH Radiotherapy
Fengmiao Bian, Jiulong Liu, Xiaoqun Zhang +2
Radiation therapy (RT) aims to deliver tumoricidal doses with minimal radiation-induced normal-tissue toxicity. Compared to conventional RT (of conventional dose rate), FLASH-RT (o…
A Preconditioned Riemannian Gradient Descent Algorithm for Low-Rank Matrix Recovery
Fengmiao Bian, Jian-Feng Cai, Rui Zhang
The low-rank matrix recovery problem often arises in various fields, including signal processing, machine learning, and imaging science. The Riemannian gradient descent (RGD) algor…
A stochastic three-block splitting algorithm and its application to quantized deep neural networks
Fengmiao Bian, Ren Liu, Xiaoqun Zhang
Deep neural networks (DNNs) have made great progress in various fields. In particular, the quantized neural network is a promising technique making DNNs compatible on resource-limi…
A Stochastic Alternating Direction Method of Multipliers for Non-smooth and Non-convex Optimization
Fengmiao Bian, Jingwei Liang, Xiaoqun Zhang
Alternating direction method of multipliers (ADMM) is a popular first-order method owing to its simplicity and efficiency. However, similar to other proximal splitting methods, the…
A three-operator splitting algorithm for nonconvex sparsity regularization
Fengmiao Bian, Xiaoqun Zhang
Sparsity regularization has been largely applied in many fields, such as signal and image processing and machine learning. In this paper, we mainly consider nonconvex minimization…
A parameterized Douglas-Rachford Splitting algorithm for nonconvex optimization
Fengmiao Bian, Xiaoqun Zhang
In this paper, we study a parameterized Douglas-Rachford splitting method for a class of nonconvex optimization problem. A new merit function is constructed to establish the conver…