activity
20222025
most citedFedHPO-B: A Benchmark Suite for Federated Hyperparameter Optimization

6 citations · 13 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2025

VeriSciQA: An Auto-Verified Dataset for Scientific Visual Question Answering

Yuyi Li, Daoyuan Chen, Zhen Wang +2

Large Vision-Language Models (LVLMs) show promise for scientific applications, yet open-source models still struggle with Scientific Visual Question Answering (SVQA), namely answer…

cs.LG2025

ReDiSC: A Reparameterized Masked Diffusion Model for Scalable Node Classification with Structured Predictions

Yule Li, Yifeng Lu, Zhen Wang +3

In recent years, graph neural networks (GNN) have achieved unprecedented successes in node classification tasks. Although GNNs inherently encode specific inductive biases (e.g., ac…

cs.LG2023★ 3 cited

HPN: Personalized Federated Hyperparameter Optimization

Anda Cheng, Zhen Wang, Yaliang Li +1

Numerous research studies in the field of federated learning (FL) have attempted to use personalization to address the heterogeneity among clients, one of FL's most crucial and cha…

cs.LG2023★ 1 cited

LON-GNN: Spectral GNNs with Learnable Orthonormal Basis

Qian Tao, Zhen Wang, Wenyuan Yu +2

In recent years, a plethora of spectral graph neural networks (GNN) methods have utilized polynomial basis with learnable coefficients to achieve top-tier performances on many node…

cs.LG2022★ 3 cited

A Benchmark for Federated Hetero-Task Learning

Liuyi Yao, Dawei Gao, Zhen Wang +7

To investigate the heterogeneity in federated learning in real-world scenarios, we generalize the classic federated learning to federated hetero-task learning, which emphasizes the…

cs.LG2022★ 6 cited

FedHPO-B: A Benchmark Suite for Federated Hyperparameter Optimization

Zhen Wang, Weirui Kuang, Ce Zhang +2

Hyperparameter optimization (HPO) is crucial for machine learning algorithms to achieve satisfactory performance, whose progress has been boosted by related benchmarks. Nonetheless…