activity
20222026
most citedPAPM: A Physics-aware Proxy Model for Process Systems

2 citations · 2 across the 6 of their papers we have counts for

collaborators

7 papers

cs.LG2026

A Moving-Horizon Approximate Branch-and-Reduce Method for Deep Classification Trees

Chenxuanyin Zou, Jiayang Ren, Qiangqiang Mao +3

Despite the importance for interpretability, decision trees face severe scalability challenges. Existing global optimal methods are often limited by binary feature selection and sh…

cs.LG2026

Continual Learning with Elastic Regularization and Synthetic Replay for Federated MLLM Fine-Tuning

Jing Liu, Chenxuanyin Zou, Jiayang Ren +5

Federated fine-tuning of Multimodal Large Language Models (MLLMs) across distributed networks enables privacy-sensitive adaptation to evolving data streams, yet a fundamental obsta…

math.OC2025

Exact Learning of Linear Model Predictive Control Laws using Oblique Decision Trees with Linear Predictions

Jiayang Ren, Qiangqiang Mao, Tianwei Zhao +1

Model Predictive Control (MPC) is a powerful strategy for constrained multivariable systems but faces computational challenges in real-time deployment due to its online optimizatio…

cs.LG2024★ 2 cited

PAPM: A Physics-aware Proxy Model for Process Systems

Pengwei Liu, Zhongkai Hao, Xingyu Ren +3

In the context of proxy modeling for process systems, traditional data-driven deep learning approaches frequently encounter significant challenges, such as substantial training cos…

cs.LG2023

A GPU-Accelerated Moving-Horizon Algorithm for Training Deep Classification Trees on Large Datasets

Jiayang Ren, Valentín Osuna-Enciso, Morimasa Okamoto +5

Decision trees are essential yet NP-complete to train, prompting the widespread use of heuristic methods such as CART, which suffers from sub-optimal performance due to its greedy…

math.OC2023

A Global Optimization Algorithm for K-Center Clustering of One Billion Samples

Jiayang Ren, Ningning You, Kaixun Hua +2

This paper presents a practical global optimization algorithm for the K-center clustering problem, which aims to select K samples as the cluster centers to minimize the maximum wit…

eess.SY2022

Deep Learning-based Predictive Control of Battery Management for Frequency Regulation

Yun Li, Yixiu Wang, Yifu Chen +5

This paper proposes a deep learning-based optimal battery management scheme for frequency regulation (FR) by integrating model predictive control (MPC), supervised learning (SL), r…