Kaixiong Zhou

Publication Activity (10 Years)

Years Active: 2015-2023
Publications (10 Years): 72

Top Topics

Outlier Detection

Graph Representation

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Top Venues

Publications

Tianlong Chen, Kaixiong Zhou, Keyu Duan, Wenqing Zheng, Peihao Wang, Xia Hu, Zhangyang Wang
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study. IEEE Trans. Pattern Anal. Mach. Intell. 45 (3) (2023)
Xuansheng Wu, Kaixiong Zhou, Mingchen Sun, Xin Wang, Ninghao Liu
A Survey of Graph Prompting Methods: Techniques, Applications, and Challenges. CoRR (2023)
Huiyuan Chen, Kaixiong Zhou, Kwei-Herng Lai, Chin-Chia Michael Yeh, Yan Zheng, Xia Hu, Hao Yang
Hessian-aware Quantized Node Embeddings for Recommendation. CoRR (2023)
Yu-Neng Chuang, Guanchu Wang, Chia-Yuan Chang, Kwei-Herng Lai, Daochen Zha, Ruixiang Tang, Fan Yang, Alfredo Costilla-Reyes, Kaixiong Zhou, Xiaoqian Jiang, Xia Ben Hu
DiscoverPath: A Knowledge Refinement and Retrieval System for Interdisciplinarity on Biomedical Research. CoRR (2023)
Kwei-Herng Lai, Lan Wang, Huiyuan Chen, Kaixiong Zhou, Fei Wang, Hao Yang, Xia Hu
Context-aware Domain Adaptation for Time Series Anomaly Detection. CoRR (2023)
Yucheng Shi, Kaixiong Zhou, Ninghao Liu
ENGAGE: Explanation Guided Data Augmentation for Graph Representation Learning. ECML/PKDD (3) (2023)
Zirui Liu, Shengyuan Chen, Kaixiong Zhou, Daochen Zha, Xiao Huang, Xia Hu
RSC: Accelerate Graph Neural Networks Training via Randomized Sparse Computations. ICML (2023)
Huiyuan Chen, Kaixiong Zhou, Kwei-Herng Lai, Chin-Chia Michael Yeh, Yan Zheng, Xia Hu, Hao Yang
Hessian-aware Quantized Node Embeddings for Recommendation. RecSys (2023)
Guanchu Wang, Yu-Neng Chuang, Fan Yang, Mengnan Du, Chia-Yuan Chang, Shaochen Zhong, Zirui Liu, Zhaozhuo Xu, Kaixiong Zhou, Xuanting Cai, Xia Hu
LETA: Learning Transferable Attribution for Generic Vision Explainer. CoRR (2023)
Hengrui Gu, Kaixiong Zhou, Xiaotian Han, Ninghao Liu, Ruobing Wang, Xin Wang
PokeMQA: Programmable knowledge editing for Multi-hop Question Answering. CoRR (2023)
Kaixiong Zhou, Soo-Hyun Choi, Zirui Liu, Ninghao Liu, Fan Yang, Rui Chen, Li Li, Xia Hu
Adaptive Label Smoothing To Regularize Large-Scale Graph Training. SDM (2023)
Huiyuan Chen, Kaixiong Zhou, Zhimeng Jiang, Chin-Chia Michael Yeh, Xiaoting Li, Menghai Pan, Yan Zheng, Xia Hu, Hao Yang
Probabilistic Masked Attention Networks for Explainable Sequential Recommendation. IJCAI (2023)
Zhaozhuo Xu, Zirui Liu, Beidi Chen, Yuxin Tang, Jue Wang, Kaixiong Zhou, Xia Hu, Anshumali Shrivastava
Compress, Then Prompt: Improving Accuracy-Efficiency Trade-off of LLM Inference with Transferable Prompt. CoRR (2023)
Zirui Liu, Guanchu Wang, Shaochen (Henry) Zhong, Zhaozhuo Xu, Daochen Zha, Ruixiang (Ryan) Tang, Zhimeng Stephen Jiang, Kaixiong Zhou, Vipin Chaudhary, Shuai Xu, Xia Hu
Winner-Take-All Column Row Sampling for Memory Efficient Adaptation of Language Model. NeurIPS (2023)
Kwei-Herng Lai, Lan Wang, Huiyuan Chen, Kaixiong Zhou, Fei Wang, Hao Yang, Xia Hu
Context-aware Domain Adaptation for Time Series Anomaly Detection. SDM (2023)
Yu-Neng Chuang, Guanchu Wang, Chia-Yuan Chang, Kwei-Herng Lai, Daochen Zha, Ruixiang Tang, Fan Yang, Alfredo Costilla-Reyes, Kaixiong Zhou, Xiaoqian Jiang, Xia Hu
DiscoverPath: A Knowledge Refinement and Retrieval System for Interdisciplinarity on Biomedical Research. CIKM (2023)
Yucheng Shi, Kaixiong Zhou, Ninghao Liu
ENGAGE: Explanation Guided Data Augmentation for Graph Representation Learning. CoRR (2023)
Xiaotian Han, Kaixiong Zhou, Ting-Hsiang Wang, Jundong Li, Fei Wang, Na Zou
Marginal Nodes Matter: Towards Structure Fairness in Graphs. CoRR (2023)
Zirui Liu, Guanchu Wang, Shaochen Zhong, Zhaozhuo Xu, Daochen Zha, Ruixiang Tang, Zhimeng Jiang, Kaixiong Zhou, Vipin Chaudhary, Shuai Xu, Xia Hu
Winner-Take-All Column Row Sampling for Memory Efficient Adaptation of Language Model. CoRR (2023)
Zhimeng Jiang, Kaixiong Zhou, Mi Zhang, Rui Chen, Xia Hu, Soo-Hyun Choi
Adaptive RiskAware Bidding with Budget Constraint in Display Advertising. SIGKDD Explor. 25 (1) (2023)
Zirui Liu, Zhimeng Jiang, Shaochen Zhong, Kaixiong Zhou, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu
Editable Graph Neural Network for Node Classifications. CoRR (2023)
Daochen Zha, Kwei-Herng Lai, Kaixiong Zhou, Xia Hu
Towards Similarity-Aware Time-Series Classification. SDM (2022)
Zhimeng Jiang, Kaixiong Zhou, Zirui Liu, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu
An Information Fusion Approach to Learning with Instance-Dependent Label Noise. ICLR (2022)
Mingchen Sun, Kaixiong Zhou, Xin He, Ying Wang, Xin Wang
GPPT: Graph Pre-training and Prompt Tuning to Generalize Graph Neural Networks. KDD (2022)
Kaixiong Zhou, Zirui Liu, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu
Table2Graph: Transforming Tabular Data to Unified Weighted Graph. IJCAI (2022)
Yili Wang, Kaixiong Zhou, Rui Miao, Ninghao Liu, Xin Wang
AdaGCL: Adaptive Subgraph Contrastive Learning to Generalize Large-scale Graph Training. CIKM (2022)
Cameron Diao, Kaixiong Zhou, Xiao Huang, Xia Hu
MolCPT: Molecule Continuous Prompt Tuning to Generalize Molecular Representation Learning. CoRR (2022)
Huiyuan Chen, Xiaoting Li, Kaixiong Zhou, Xia Hu, Chin-Chia Michael Yeh, Yan Zheng, Hao Yang
TinyKG: Memory-Efficient Training Framework for Knowledge Graph Neural Recommender Systems. CoRR (2022)
Keyu Duan, Zirui Liu, Peihao Wang, Wenqing Zheng, Kaixiong Zhou, Tianlong Chen, Xia Hu, Zhangyang Wang
A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking. CoRR (2022)
Kaixiong Zhou, Xiao Huang, Qingquan Song, Rui Chen, Xia Hu
Auto-GNN: Neural architecture search of graph neural networks. Frontiers Big Data 5 (2022)
Zhimeng Jiang, Kaixiong Zhou, Mi Zhang, Rui Chen, Xia Hu, Soo-Hyun Choi
Adaptive Risk-Aware Bidding with Budget Constraint in Display Advertising. CoRR (2022)
Zirui Liu, Shengyuan Chen, Kaixiong Zhou, Daochen Zha, Xiao Huang, Xia Hu
RSC: Accelerating Graph Neural Networks Training via Randomized Sparse Computations. CoRR (2022)
Duc N. M. Hoang, Kaixiong Zhou, Tianlong Chen, Xia Hu, Zhangyang Wang
AutoCoG: A Unified Data-Model Co-Search Framework for Graph Neural Networks. AutoML (2022)
Yuening Li, Zhengzhang Chen, Daochen Zha, Kaixiong Zhou, Haifeng Jin, Haifeng Chen, Xia Hu
Automated Anomaly Detection via Curiosity-Guided Search and Self-Imitation Learning. IEEE Trans. Neural Networks Learn. Syst. 33 (6) (2022)
Keyu Duan, Zirui Liu, Peihao Wang, Wenqing Zheng, Kaixiong Zhou, Tianlong Chen, Xia Hu, Zhangyang Wang
A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking. NeurIPS (2022)
Kaixiong Zhou, Zhenyu Zhang, Shengyuan Chen, Tianlong Chen, Xiao Huang, Zhangyang Wang, Xia Hu
QuanGCN: Noise-Adaptive Training for Robust Quantum Graph Convolutional Networks. CoRR (2022)
Kai Guo, Kaixiong Zhou, Xia Hu, Yu Li, Yi Chang, Xin Wang
Orthogonal Graph Neural Networks. AAAI (2022)
Zirui Liu, Kaixiong Zhou, Fan Yang, Li Li, Rui Chen, Xia Hu
EXACT: Scalable Graph Neural Networks Training via Extreme Activation Compression. ICLR (2022)
Huiyuan Chen, Xiaoting Li, Kaixiong Zhou, Xia Hu, Chin-Chia Michael Yeh, Yan Zheng, Hao Yang
TinyKG: Memory-Efficient Training Framework for Knowledge Graph Neural Recommender Systems. RecSys (2022)
Fan Yang, Qizhang Feng, Kaixiong Zhou, Jiahao Chen, Xia Hu
Differentially Private Counterfactuals via Functional Mechanism. CoRR (2022)
Daochen Zha, Kwei-Herng Lai, Kaixiong Zhou, Xia Hu
Towards Similarity-Aware Time-Series Classification. CoRR (2022)
Huiyuan Chen, Kaixiong Zhou, Kwei-Herng Lai, Xia Hu, Fei Wang, Hao Yang
Adversarial Graph Perturbations for Recommendations at Scale. SIGIR (2022)
Haotian Xue, Kaixiong Zhou, Tianlong Chen, Kai Guo, Xia Hu, Yi Chang, Xin Wang
CAP: Co-Adversarial Perturbation on Weights and Features for Improving Generalization of Graph Neural Networks. CoRR (2021)
Zirui Liu, Haifeng Jin, Ting-Hsiang Wang, Kaixiong Zhou, Xia Hu
DivAug: Plug-in Automated Data Augmentation with Explicit Diversity Maximization. CoRR (2021)
Huachi Zhou, Qiaoyu Tan, Xiao Huang, Kaixiong Zhou, Xiaoling Wang
Temporal Augmented Graph Neural Networks for Session-Based Recommendations. SIGIR (2021)
Tianlong Chen, Kaixiong Zhou, Keyu Duan, Wenqing Zheng, Peihao Wang, Xia Hu, Zhangyang Wang
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study. CoRR (2021)
Daochen Zha, Kwei-Herng Lai, Kaixiong Zhou, Xia Hu
Simplifying Deep Reinforcement Learning via Self-Supervision. CoRR (2021)
Zirui Liu, Haifeng Jin, Ting-Hsiang Wang, Kaixiong Zhou, Xia Hu
DivAug: Plug-in Automated Data Augmentation with Explicit Diversity Maximization. ICCV (2021)
Kaixiong Zhou, Xiao Huang, Daochen Zha, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu
Dirichlet Energy Constrained Learning for Deep Graph Neural Networks. CoRR (2021)
Yuening Li, Zhengzhang Chen, Daochen Zha, Kaixiong Zhou, Haifeng Jin, Haifeng Chen, Xia Hu
AutoOD: Neural Architecture Search for Outlier Detection. ICDE (2021)
Kai Guo, Kaixiong Zhou, Xia Hu, Yu Li, Yi Chang, Xin Wang
Orthogonal Graph Neural Networks. CoRR (2021)
Kaixiong Zhou, Ninghao Liu, Fan Yang, Zirui Liu, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu
Adaptive Label Smoothing To Regularize Large-Scale Graph Training. CoRR (2021)
Kaixiong Zhou, Xiao Huang, Daochen Zha, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu
Dirichlet Energy Constrained Learning for Deep Graph Neural Networks. NeurIPS (2021)
Fan Yang, Ninghao Liu, Mengnan Du, Kaixiong Zhou, Shuiwang Ji, Xia Hu
Deep Neural Networks with Knowledge Instillation. SDM (2020)
Zirui Liu, Qingquan Song, Kaixiong Zhou, Ting-Hsiang Wang, Ying Shan, Xia Hu
Detecting Interactions from Neural Networks via Topological Analysis. NeurIPS (2020)
Kaixiong Zhou, Xiao Huang, Yuening Li, Daochen Zha, Rui Chen, Xia Hu
Towards Deeper Graph Neural Networks with Differentiable Group Normalization. NeurIPS (2020)
Kaixiong Zhou, Xiao Huang, Yuening Li, Daochen Zha, Rui Chen, Xia Hu
Towards Deeper Graph Neural Networks with Differentiable Group Normalization. CoRR (2020)
Kaixiong Zhou, Qingquan Song, Xiao Huang, Daochen Zha, Na Zou, Xia Hu
Multi-Channel Graph Neural Networks. IJCAI (2020)
Kwei-Herng Lai, Daochen Zha, Kaixiong Zhou, Xia Hu
Policy-GNN: Aggregation Optimization for Graph Neural Networks. KDD (2020)
Zirui Liu, Qingquan Song, Kaixiong Zhou, Ting-Hsiang Wang, Ying Shan, Xia Hu
Towards Interaction Detection Using Topological Analysis on Neural Networks. CoRR (2020)
Kwei-Herng Lai, Daochen Zha, Kaixiong Zhou, Xia Hu
Policy-GNN: Aggregation Optimization for Graph Neural Networks. CoRR (2020)
Yuening Li, Zhengzhang Chen, Daochen Zha, Kaixiong Zhou, Haifeng Jin, Haifeng Chen, Xia Hu
AutoOD: Automated Outlier Detection via Curiosity-guided Search and Self-imitation Learning. CoRR (2020)
Kaixiong Zhou, Qingquan Song, Xiao Huang, Daochen Zha, Na Zou, Xia Hu
Multi-Channel Graph Convolutional Networks. CoRR (2019)
Daochen Zha, Kwei-Herng Lai, Kaixiong Zhou, Xia Hu
Experience Replay Optimization. IJCAI (2019)
Daochen Zha, Kwei-Herng Lai, Kaixiong Zhou, Xia Hu
Experience Replay Optimization. CoRR (2019)
Kaixiong Zhou, Qingquan Song, Xiao Huang, Xia Hu
Auto-GNN: Neural Architecture Search of Graph Neural Networks. CoRR (2019)
Kaixiong Zhou, Chen Gong, Nan Wu, Zhengyuan Xu
Distributed Channel Allocation and Rate Control for Hybrid FSO/RF Vehicular Ad Hoc Networks. JOCN 9 (8) (2017)
Mian Zeng, Kaixiong Zhou, Chen Gong, Shun Lou, Xianqing Jin, Zhengyuan Xu
Design and demonstration of an indoor visible light communication network with dynamic user access and resource allocation. WCSP (2017)
Xin Huang, Kaixiong Zhou, Chao Xiang Shi, Jian Xin Chang, Meng Gao
Transmissions and Network Management of Multiple 100 GB/s Based on Stacking Technology. ChinaCom (2) (2017)
Kaixiong Zhou, Xin Huang, Chao Xiang Shi, Jian Xin Chang, Meng Gao
Design and implementation of a novel 100G optical interface protocol converter. WCSP (2017)
Kaixiong Zhou, Chen Gong, Qian Gao, Zhengyuan Xu
Inter-cell interference coordination for multi-color visible light communication networks. GlobalSIP (2016)
Kaixiong Zhou, Lin Zhang, Ming Jiang
Enhanced effective SNR prediction for LTE downlink. ICCC (2015)