activity
20212026
most citedLook Beneath the Surface: Exploiting Fundamental Symmetry for Sample-Efficient Offline RL

2 citations · 3 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2026

FedTopo: Relation-Level Topology Sharing for Model-Heterogeneous Federated Learning

Zhaoyang Ma, Zhihao Wu, Xin Gao +3

Federated learning (FL) enables collaborative learning over decentralized data silos without centralizing raw data. However, heterogeneous local architectures often induce non-alig…

cs.LG2025

Harmonizing Intra-coherence and Inter-divergence in Ensemble Attacks for Adversarial Transferability

Zhaoyang Ma, Zhihao Wu, Wang Lu +6

The development of model ensemble attacks has significantly improved the transferability of adversarial examples, but this progress also poses severe threats to the security of dee…

cs.CV2023★ 1 cited

Building Category Graphs Representation with Spatial and Temporal Attention for Visual Navigation

Xiaobo Hu, Youfang Lin, HeHe Fan +3

Given an object of interest, visual navigation aims to reach the object's location based on a sequence of partial observations. To this end, an agent needs to 1) learn a piece of c…

cs.LG2023★ 2 cited

Look Beneath the Surface: Exploiting Fundamental Symmetry for Sample-Efficient Offline RL

Peng Cheng, Xianyuan Zhan, Zhihao Wu +5

Offline reinforcement learning (RL) offers an appealing approach to real-world tasks by learning policies from pre-collected datasets without interacting with the environment. Howe…

cs.CV2021

Agent-Centric Relation Graph for Object Visual Navigation

Xiaobo Hu, Youfang Lin, Shuo Wang +2

Object visual navigation aims to steer an agent toward a target object based on visual observations. It is highly desirable to reasonably perceive the environment and accurately co…

cs.AI2021

Analyzing Wikipedia Membership Dataset and PredictingUnconnected Nodes in the Signed Networks

Zhihao Wu, Taoran Li, Ray Roman

In the age of digital interaction, person-to-person relationships existing on social media may be different from the very same interactions that exist offline. Examining potential…