activity
20202024
most citedFedCluster: Boosting the Convergence of Federated Learning via Cluster-Cycling

55 citations · 155 across the 32 of their papers we have counts for

collaborators
Showing 2023Show all

9 papers · 1 filter

physics.geo-ph2023★ 3 cited

Numerical Simulation of the Impact of Different Cushion Gases on Underground Hydrogen Storage in Aquifers Based on an Experimentally-Benchmarked Equation-of-State

Qingqi Zhao, Yuhang Wang, Cheng Chen

Underground hydrogen storage (UHS) in geological formations is a promising technology for large-scale hydrogen energy storage. Although lessons were learned from similar studies, i…

cs.CV2023

Semantic Contrastive Bootstrapping for Single-positive Multi-label Recognition

Cheng Chen, Yifan Zhao, Jia Li

Learning multi-label image recognition with incomplete annotation is gaining popularity due to its superior performance and significant labor savings when compared to training with…

cs.LG2023

REAL: A Representative Error-Driven Approach for Active Learning

Cheng Chen, Yong Wang, Lizi Liao +2

Given a limited labeling budget, active learning (AL) aims to sample the most informative instances from an unlabeled pool to acquire labels for subsequent model training. To achie…

cs.CL2023

AI Coach Assist: An Automated Approach for Call Recommendation in Contact Centers for Agent Coaching

Md Tahmid Rahman Laskar, Cheng Chen, Xue-Yong Fu +3

In recent years, the utilization of Artificial Intelligence (AI) in the contact center industry is on the rise. One area where AI can have a significant impact is in the coaching o…

eess.IV2023

CSI-Inpainter: Enabling Visual Scene Recovery from CSI Time Sequences for Occlusion Removal

Cheng Chen, Shoki Ohta, Takayuki Nishio +3

Introducing CSI-Inpainter, a pioneering approach for occlusion removal using Channel State Information (CSI) time sequences, this work propels the application of wireless signal pr…

math.OC2023★ 1 cited

Symmetric Rank- Methods

Chengchang Liu, Cheng Chen, Luo Luo

This paper proposes a novel class of block quasi-Newton methods for convex optimization which we call symmetric rank- (SR-) methods. Each iteration of SR- incorporates the…