Search Results for author: Zhanke Zhou

Found 9 papers, 7 papers with code

Efficient Hyper-parameter Search for Knowledge Graph Embedding

1 code implementation ACL 2022 Yongqi Zhang, Zhanke Zhou, Quanming Yao, Yong Li

Based on the analysis, we propose an efficient two-stage search algorithm KGTuner, which efficiently explores HP configurations on small subgraph at the first stage and transfers the top-performed configurations for fine-tuning on the large full graph at the second stage.

AutoML Knowledge Graph Embedding

Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs

1 code implementation15 Mar 2024 Zhanke Zhou, Yongqi Zhang, Jiangchao Yao, Quanming Yao, Bo Han

To deduce new facts on a knowledge graph (KG), a link predictor learns from the graph structure and collects local evidence to find the answer to a given query.

Knowledge Graphs Link Prediction

DeepInception: Hypnotize Large Language Model to Be Jailbreaker

1 code implementation6 Nov 2023 Xuan Li, Zhanke Zhou, Jianing Zhu, Jiangchao Yao, Tongliang Liu, Bo Han

Despite remarkable success in various applications, large language models (LLMs) are vulnerable to adversarial jailbreaks that make the safety guardrails void.

Language Modelling Large Language Model

Long-Range Neural Atom Learning for Molecular Graphs

no code implementations2 Nov 2023 Xuan Li, Zhanke Zhou, Jiangchao Yao, Yu Rong, Lu Zhang, Bo Han

Graph Neural Networks (GNNs) have been widely adopted for drug discovery with molecular graphs.

Drug Discovery

Combating Bilateral Edge Noise for Robust Link Prediction

1 code implementation NeurIPS 2023 Zhanke Zhou, Jiangchao Yao, Jiaxu Liu, Xiawei Guo, Quanming Yao, Li He, Liang Wang, Bo Zheng, Bo Han

To address this dilemma, we propose an information-theory-guided principle, Robust Graph Information Bottleneck (RGIB), to extract reliable supervision signals and avoid representation collapse.

Denoising Link Prediction +1

Understanding Fairness Surrogate Functions in Algorithmic Fairness

no code implementations17 Oct 2023 Wei Yao, Zhanke Zhou, Zhicong Li, Bo Han, Yong liu

To mitigate such bias while achieving comparable accuracy, a promising approach is to introduce surrogate functions of the concerned fairness definition and solve a constrained optimization problem.

Fairness

On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation

1 code implementation15 Jun 2023 Zhanke Zhou, Chenyu Zhou, Xuan Li, Jiangchao Yao, Quanming Yao, Bo Han

Although powerful graph neural networks (GNNs) have boosted numerous real-world applications, the potential privacy risk is still underexplored.

Graph Reconstruction Reconstruction Attack

AdaProp: Learning Adaptive Propagation for Graph Neural Network based Knowledge Graph Reasoning

2 code implementations30 May 2022 Yongqi Zhang, Zhanke Zhou, Quanming Yao, Xiaowen Chu, Bo Han

An important design component of GNN-based KG reasoning methods is called the propagation path, which contains a set of involved entities in each propagation step.

Knowledge Graphs

KGTuner: Efficient Hyper-parameter Search for Knowledge Graph Learning

2 code implementations5 May 2022 Yongqi Zhang, Zhanke Zhou, Quanming Yao, Yong Li

While hyper-parameters (HPs) are important for knowledge graph (KG) learning, existing methods fail to search them efficiently.

Graph Learning

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