activity
20192025
most citedA three-operator splitting algorithm for nonconvex sparsity regularization

1 citations · 1 across the 4 of their papers we have counts for

collaborators

7 papers

cs.LG2026

AdaPreLoRA: Adafactor Preconditioned Low-Rank Adaptation

Ziyun Liu, Fengmiao Bian, Jian-Feng Cai

Low-Rank Adaptation (LoRA) reparameterizes a weight update as a product of two low-rank factors, but the Jacobian of the generator mapping the factors to the weight matrix…

cs.LG2025

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…

math.OC2023

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…

math.OC2022

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…

math.OC2020

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…

math.OC20201 cited

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…