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ORCIDBryan Hooi
Bryan Hooi Kuen-Yew
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- affiliation: National University of Singapore, Singapore
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2020 – today
- 2025
[c115]Cheng Wang, Yiwei Wang, Bryan Hooi, Yujun Cai, Nanyun Peng, Kai-Wei Chang:
Con-ReCall: Detecting Pre-training Data in LLMs via Contrastive Decoding. COLING 2025: 1013-1026- 2024
- [j20]Jun Hu
, Bryan Hooi, Shengsheng Qian, Quan Fang, Changsheng Xu:
MGDCF: Distance Learning via Markov Graph Diffusion for Neural Collaborative Filtering. IEEE Trans. Knowl. Data Eng. 36(7): 3281-3296 (2024) - [j19]Wenjie Feng, Li Wang, Bryan Hooi, See-Kiong Ng, Shenghua Liu:
Interrelated Dense Pattern Detection in Multilayer Networks. IEEE Trans. Knowl. Data Eng. 36(11): 6462-6476 (2024) - [j18]Jun Hu, Bryan Hooi, Bingsheng He:
Efficient Heterogeneous Graph Learning via Random Projection. IEEE Trans. Knowl. Data Eng. 36(12): 8093-8107 (2024) - [j17]Chenming Yang, Hui Wen, Bryan Hooi, Liang Zhou:
CapMax: A Framework for Dynamic Network Representation Learning From the View of Multiuser Communication. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4554-4566 (2024) - [c114]Zhiyuan Hu, Chumin Liu, Yue Feng, Anh Tuan Luu, Bryan Hooi:
PoetryDiffusion: Towards Joint Semantic and Metrical Manipulation in Poetry Generation. AAAI 2024: 18279-18288 - [c113]Jintian Zhang, Xin Xu, Ningyu Zhang, Ruibo Liu, Bryan Hooi, Shumin Deng:
Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology View. ACL (1) 2024: 14544-14607 - [c112]Hewen Wang, Bryan Hooi, Dan He, Juncheng Liu, Xiaokui Xiao:
EGNN-AD: An Effective Graph Neural Network-Based Approach for Anomaly Detection on Edge-Attributed Graphs. DASFAA (6) 2024: 321-331 - [c111]Jihai Zhang, Xiang Lan, Xiaoye Qu, Yu Cheng, Mengling Feng, Bryan Hooi:
Learning the Unlearned: Mitigating Feature Suppression in Contrastive Learning. ECCV (83) 2024: 35-52 - [c110]Nan Chen, Zemin Liu, Bryan Hooi, Bingsheng He, Rizal Fathony, Jun Hu, Jia Chen:
Consistency Training with Learnable Data Augmentation for Graph Anomaly Detection with Limited Supervision. ICLR 2024 - [c109]Xiaoxin He, Xavier Bresson, Thomas Laurent, Adam Perold, Yann LeCun, Bryan Hooi:
Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning. ICLR 2024 - [c108]Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Yiwei Wang, Chaosheng Dong, Xiaokui Xiao:
Scalable and Effective Implicit Graph Neural Networks on Large Graphs. ICLR 2024 - [c107]Miao Xiong, Zhiyuan Hu, Xinyang Lu, Yifei Li, Jie Fu, Junxian He, Bryan Hooi:
Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs. ICLR 2024 - [c106]Wei Zhuo, Zemin Liu, Bryan Hooi, Bingsheng He, Guang Tan, Rizal Fathony, Jia Chen:
Partitioning Message Passing for Graph Fraud Detection. ICLR 2024 - [c105]Adrien Benamira, Thomas Peyrin, Trevor Yap, Tristan Guérand, Bryan Hooi:
Truth Table Net: Scalable, Compact & Verifiable Neural Networks with a Dual Convolutional Small Boolean Circuit Networks Form. IJCAI 2024: 13-21 - [c104]Jiaying Wu, Jiafeng Guo, Bryan Hooi:
Fake News in Sheep's Clothing: Robust Fake News Detection Against LLM-Empowered Style Attacks. KDD 2024: 3367-3378 - [c103]Xu Liu, Yuxuan Liang, Chao Huang, Hengchang Hu, Yushi Cao, Bryan Hooi, Roger Zimmermann:
Reinventing Node-centric Traffic Forecasting for Improved Accuracy and Efficiency. ECML/PKDD (3) 2024: 21-38 - [c102]Yuexin Li, Chengyu Huang, Shumin Deng, Mei Lin Lock, Tri Cao, Nay Oo, Hoon Wei Lim, Bryan Hooi:
KnowPhish: Large Language Models Meet Multimodal Knowledge Graphs for Enhancing Reference-Based Phishing Detection. USENIX Security Symposium 2024 - [c101]Haitao Mao, Jianan Zhao, Xiaoxin He, Zhikai Chen, Qian Huang, Zhaocheng Zhu, Jian Tang, Michael M. Bronstein, Xavier Bresson, Bryan Hooi, Haiyang Zhang, Xianfeng Tang, Luo Chen, Jiliang Tang:
The 1st International Workshop on Graph Foundation Models (GFM). WWW (Companion Volume) 2024: 1789-1792 - [c100]Xu Liu, Junfeng Hu, Yuan Li, Shizhe Diao, Yuxuan Liang, Bryan Hooi, Roger Zimmermann:
UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecasting. WWW 2024: 4095-4106 - [i117]Zhiyuan Hu, Chumin Liu, Xidong Feng, Yilun Zhao, See-Kiong Ng, Anh Tuan Luu, Junxian He, Pang Wei Koh, Bryan Hooi:
Uncertainty of Thoughts: Uncertainty-Aware Planning Enhances Information Seeking in Large Language Models. CoRR abs/2402.03271 (2024) - [i116]Xiaoxin He, Yijun Tian, Yifei Sun, Nitesh V. Chawla, Thomas Laurent, Yann LeCun, Xavier Bresson, Bryan Hooi:
G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering. CoRR abs/2402.07630 (2024) - [i115]Jihai Zhang, Xiang Lan, Xiaoye Qu, Yu Cheng, Mengling Feng, Bryan Hooi:
Learning the Unlearned: Mitigating Feature Suppression in Contrastive Learning. CoRR abs/2402.11816 (2024) - [i114]Yufei He, Bryan Hooi:
UniGraph: Learning a Cross-Domain Graph Foundation Model From Natural Language. CoRR abs/2402.13630 (2024) - [i113]Ailin Deng, Zhirui Chen, Bryan Hooi:
Seeing is Believing: Mitigating Hallucination in Large Vision-Language Models via CLIP-Guided Decoding. CoRR abs/2402.15300 (2024) - [i112]Yuexin Li, Chengyu Huang, Shumin Deng, Mei Lin Lock, Tri Cao, Nay Oo, Bryan Hooi, Hoon Wei Lim:
KnowPhish: Large Language Models Meet Multimodal Knowledge Graphs for Enhancing Reference-Based Phishing Detection. CoRR abs/2403.02253 (2024) - [i111]Yuan Sui, Yufei He, Nian Liu, Xiaoxin He, Kun Wang, Bryan Hooi:
FiDeLiS: Faithful Reasoning in Large Language Model for Knowledge Graph Question Answering. CoRR abs/2405.13873 (2024) - [i110]Juncheng Liu, Chenghao Liu, Gerald Woo, Yiwei Wang, Bryan Hooi, Caiming Xiong, Doyen Sahoo:
UniTST: Effectively Modeling Inter-Series and Intra-Series Dependencies for Multivariate Time Series Forecasting. CoRR abs/2406.04975 (2024) - [i109]Rishabh Anand, Chaitanya K. Joshi, Alex Morehead, Arian R. Jamasb, Charles Harris, Simon V. Mathis, Kieran Didi, Bryan Hooi, Pietro Liò:
RNA-FrameFlow: Flow Matching for de novo 3D RNA Backbone Design. CoRR abs/2406.13839 (2024) - [i108]Yufei He, Zhenyu Hou, Yukuo Cen, Feng He, Xu Cheng, Bryan Hooi:
Generalizing Graph Transformers Across Diverse Graphs and Tasks via Pre-Training on Industrial-Scale Data. CoRR abs/2407.03953 (2024) - [i107]Adam Goodge, Bryan Hooi, Wee Siong Ng:
When Text and Images Don't Mix: Bias-Correcting Language-Image Similarity Scores for Anomaly Detection. CoRR abs/2407.17083 (2024) - [i106]Huilin Wang, Bryan Hooi:
Automated Phishing Detection Using URLs and Webpages. CoRR abs/2408.01667 (2024) - [i105]Jehyun Lee, Peiyuan Lim, Bryan Hooi, Dinil Mon Divakaran:
Multimodal Large Language Models for Phishing Webpage Detection and Identification. CoRR abs/2408.05941 (2024) - [i104]Tri Cao, Chengyu Huang, Yuexin Li, Huilin Wang, Amy He, Nay Oo, Bryan Hooi:
PhishAgent: A Robust Multimodal Agent for Phishing Webpage Detection. CoRR abs/2408.10738 (2024) - [i103]Zhiyuan Hu, Yuliang Liu, Jinman Zhao, Suyuchen Wang, Yan Wang, Wei Shen, Qing Gu, Anh Tuan Luu, See-Kiong Ng, Zhiwei Jiang, Bryan Hooi:
LongRecipe: Recipe for Efficient Long Context Generalization in Large Language Models. CoRR abs/2409.00509 (2024) - [i102]Cheng Wang, Yiwei Wang, Bryan Hooi, Yujun Cai, Nanyun Peng, Kai-Wei Chang:
Con-ReCall: Detecting Pre-training Data in LLMs via Contrastive Decoding. CoRR abs/2409.03363 (2024) - [i101]Shen Li, Jianqing Xu, Jiaying Wu, Miao Xiong, Ailin Deng, Jiazhen Ji, Yuge Huang, Wenjie Feng, Shouhong Ding, Bryan Hooi:
ID3: Identity-Preserving-yet-Diversified Diffusion Models for Synthetic Face Recognition. CoRR abs/2409.17576 (2024) - [i100]Yue Liu, Xiaoxin He, Miao Xiong, Jinlan Fu, Shumin Deng, Bryan Hooi:
FlipAttack: Jailbreak LLMs via Flipping. CoRR abs/2410.02832 (2024) - [i99]Yuan Sui, Bryan Hooi:
Can Knowledge Graphs Make Large Language Models More Trustworthy? An Empirical Study over Open-ended Question Answering. CoRR abs/2410.08085 (2024) - [i98]Zhecheng Li, Yiwei Wang, Bryan Hooi, Yujun Cai, Zhen Xiong, Nanyun Peng, Kai-Wei Chang:
Vulnerability of LLMs to Vertically Aligned Text Manipulations. CoRR abs/2410.20016 (2024) - [i97]Zhecheng Li, Yiwei Wang, Bryan Hooi, Yujun Cai, Naifan Cheung, Nanyun Peng, Kai-Wei Chang:
Think Carefully and Check Again! Meta-Generation Unlocking LLMs for Low-Resource Cross-Lingual Summarization. CoRR abs/2410.20021 (2024) - [i96]Yulin Chen, Haoran Li, Zihao Zheng, Yangqiu Song, Dekai Wu, Bryan Hooi:
Defense Against Prompt Injection Attack by Leveraging Attack Techniques. CoRR abs/2411.00459 (2024) - [i95]Tri Cao, Minh-Huy Trinh, Ailin Deng, Quoc-Nam Nguyen, Khoa Duong, Ngai-Man Cheung, Bryan Hooi:
Are Anomaly Scores Telling the Whole Story? A Benchmark for Multilevel Anomaly Detection. CoRR abs/2411.14515 (2024) - [i94]Zhecheng Li, Yiwei Wang, Bryan Hooi, Yujun Cai, Nanyun Peng, Kai-Wei Chang:
DRS: Deep Question Reformulation With Structured Output. CoRR abs/2411.17993 (2024) - [i93]Shuyang Hao, Bryan Hooi, Jun Liu, Kai-Wei Chang, Zi Huang, Yujun Cai:
Exploring Visual Vulnerabilities via Multi-Loss Adversarial Search for Jailbreaking Vision-Language Models. CoRR abs/2411.18000 (2024) - [i92]Wei Zhuo, Zemin Liu, Bryan Hooi, Bingsheng He, Guang Tan, Rizal Fathony, Jia Chen:
Partitioning Message Passing for Graph Fraud Detection. CoRR abs/2412.00020 (2024) - [i91]Yuexin Li, Hiok Kuek Tan, Qiaoran Meng, Mei Lin Lock, Tri Cao, Shumin Deng, Nay Oo, Hoon Wei Lim, Bryan Hooi:
PhishIntel: Toward Practical Deployment of Reference-based Phishing Detection. CoRR abs/2412.09057 (2024) - [i90]Jun Hu, Bryan Hooi, Bingsheng He, Yinwei Wei:
Modality-Independent Graph Neural Networks with Global Transformers for Multimodal Recommendation. CoRR abs/2412.13994 (2024) - 2023
- [j16]Chenming Yang, Hui Wen, Bryan Hooi, Yue Wu, Liang Zhou:
A multi-scale reconstruction method for the anomaly detection in stochastic dynamic networks. Neurocomputing 518: 482-495 (2023) - [j15]Chenming Yang, Jingjing Li, Ke Lu, Bryan Hooi, Liang Zhou:
Continuous-time graph directed information maximization for temporal network representation. Inf. Sci. 644: 119240 (2023) - [j14]Shubhranshu Shekhar, Dhivya Eswaran, Bryan Hooi, Jonathan Elmer, Christos Faloutsos, Leman Akoglu:
Benefit-aware early prediction of health outcomes on multivariate EEG time series. J. Biomed. Informatics 139: 104296 (2023) - [j13]Yifan Zhang, Bingyi Kang, Bryan Hooi, Shuicheng Yan, Jiashi Feng:
Deep Long-Tailed Learning: A Survey. IEEE Trans. Pattern Anal. Mach. Intell. 45(9): 10795-10816 (2023) - [j12]Shenghua Liu, Bin Zhou, Quan Ding, Bryan Hooi, Zhengbo Zhang, Huawei Shen, Xueqi Cheng:
Time Series Anomaly Detection With Adversarial Reconstruction Networks. IEEE Trans. Knowl. Data Eng. 35(4): 4293-4306 (2023) - [j11]Nicholas Lim, Bryan Hooi, See-Kiong Ng, Yong Liang Goh, Renrong Weng, Rui Tan:
Learning Hierarchical Spatial Tasks with Visiting Relations for Next POI Recommendation. Trans. Recomm. Syst. 1(4): 1-26 (2023) - [c99]Shumin Deng, Shengyu Mao, Ningyu Zhang, Bryan Hooi:
SPEECH: Structured Prediction with Energy-Based Event-Centric Hyperspheres. ACL (1) 2023: 351-363 - [c98]Jiaying Wu, Shen Li, Ailin Deng, Miao Xiong, Bryan Hooi:
Prompt-and-Align: Prompt-Based Social Alignment for Few-Shot Fake News Detection. CIKM 2023: 2726-2736 - [c97]Zhiyuan Hu, Yue Feng, Anh Tuan Luu, Bryan Hooi, Aldo Lipani:
Unlocking the Potential of User Feedback: Leveraging Large Language Model as User Simulators to Enhance Dialogue System. CIKM 2023: 3953-3957 - [c96]Yiwei Wang, Bryan Hooi, Fei Wang, Yujun Cai, Yuxuan Liang, Wenxuan Zhou, Jing Tang, Manjuan Duan, Muhao Chen:
How Fragile is Relation Extraction under Entity Replacements? CoNLL 2023: 414-423 - [c95]Jianqing Xu, Shen Li, Ailin Deng, Miao Xiong, Jiaying Wu, Jiaxiang Wu, Shouhong Ding, Bryan Hooi:
Probabilistic Knowledge Distillation of Face Ensembles. CVPR 2023: 3489-3498 - [c94]Yiwei Wang, Yujun Cai, Muhao Chen, Yuxuan Liang, Bryan Hooi:
Primacy Effect of ChatGPT. EMNLP 2023: 108-115 - [c93]Baixiang Huang, Bryan Hooi, Kai Shu:
TAP: A Comprehensive Data Repository for Traffic Accident Prediction in Road Networks. SIGSPATIAL/GIS 2023: 105:1-105:4 - [c92]Shumin Deng, Chengming Wang, Zhoubo Li, Ningyu Zhang, Zelin Dai, Hehong Chen, Feiyu Xiong, Ming Yan, Qiang Chen, Mosha Chen, Jiaoyan Chen, Jeff Z. Pan, Bryan Hooi, Huajun Chen:
Construction and Applications of Billion-Scale Pre-Trained Multimodal Business Knowledge Graph. ICDE 2023: 2988-3002 - [c91]Ailin Deng, Miao Xiong, Bryan Hooi:
Great Models Think Alike: Improving Model Reliability via Inter-Model Latent Agreement. ICML 2023: 7675-7693 - [c90]Xiaoxin He, Bryan Hooi, Thomas Laurent, Adam Perold, Yann LeCun, Xavier Bresson:
A Generalization of ViT/MLP-Mixer to Graphs. ICML 2023: 12724-12745 - [c89]Yuwen Li, Miao Xiong, Bryan Hooi:
GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning Benchmarks. ICML 2023: 20195-20209 - [c88]Kaixin Wang, Kuangqi Zhou, Jiashi Feng, Bryan Hooi, Xinchao Wang:
Reachability-Aware Laplacian Representation in Reinforcement Learning. ICML 2023: 36670-36693 - [c87]Mingqi Yang, Wenjie Feng, Yanming Shen, Bryan Hooi:
Towards Better Graph Representation Learning with Parameterized Decomposition & Filtering. ICML 2023: 39234-39251 - [c86]Siddharth Bhatia, Mohit Wadhwa, Kenji Kawaguchi, Neil Shah, Philip S. Yu, Bryan Hooi:
Sketch-Based Anomaly Detection in Streaming Graphs. KDD 2023: 93-104 - [c85]Jiaying Wu, Bryan Hooi:
DECOR: Degree-Corrected Social Graph Refinement for Fake News Detection. KDD 2023: 2582-2593 - [c84]Xu Liu, Yutong Xia, Yuxuan Liang, Junfeng Hu, Yiwei Wang, Lei Bai, Chao Huang, Zhenguang Liu, Bryan Hooi, Roger Zimmermann:
LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting. NeurIPS 2023 - [c83]Miao Xiong, Ailin Deng, Pang Wei W. Koh, Jiaying Wu, Shen Li, Jianqing Xu, Bryan Hooi:
Proximity-Informed Calibration for Deep Neural Networks. NeurIPS 2023 - [c82]Yifan Zhang, Daquan Zhou, Bryan Hooi, Kai Wang, Jiashi Feng:
Expanding Small-Scale Datasets with Guided Imagination. NeurIPS 2023 - [c81]Yiwei Wang, Bryan Hooi, Yozen Liu, Neil Shah:
Graph Explicit Neural Networks: Explicitly Encoding Graphs for Efficient and Accurate Inference. WSDM 2023: 348-356 - [i89]Xu Liu, Yuxuan Liang, Chao Huang, Hengchang Hu, Yushi Cao, Bryan Hooi, Roger Zimmermann:
Do We Really Need Graph Neural Networks for Traffic Forecasting? CoRR abs/2301.12603 (2023) - [i88]Ailin Deng, Shen Li, Miao Xiong, Zhirui Chen, Bryan Hooi:
Trust, but Verify: Using Self-Supervised Probing to Improve Trustworthiness. CoRR abs/2302.02628 (2023) - [i87]Aashish Kolluri, Sarthak Choudhary, Bryan Hooi, Prateek Saxena:
RETEXO: Scalable Neural Network Training over Distributed Graphs. CoRR abs/2302.13053 (2023) - [i86]Baixiang Huang, Bryan Hooi, Kai Shu:
TAP: A Comprehensive Data Repository for Traffic Accident Prediction in Road Networks. CoRR abs/2304.08640 (2023) - [i85]Ailin Deng, Miao Xiong, Bryan Hooi:
Great Models Think Alike: Improving Model Reliability via Inter-Model Latent Agreement. CoRR abs/2305.01481 (2023) - [i84]Mingqi Yang, Wenjie Feng, Yanming Shen, Bryan Hooi:
Towards Better Graph Representation Learning with Parameterized Decomposition & Filtering. CoRR abs/2305.06102 (2023) - [i83]Yiwei Wang, Bryan Hooi, Fei Wang, Yujun Cai, Yuxuan Liang, Wenxuan Zhou, Jing Tang, Manjuan Duan, Muhao Chen:
How Fragile is Relation Extraction under Entity Replacements? CoRR abs/2305.13551 (2023) - [i82]Shumin Deng, Shengyu Mao, Ningyu Zhang, Bryan Hooi:
SPEECH: Structured Prediction with Energy-Based Event-Centric Hyperspheres. CoRR abs/2305.13617 (2023) - [i81]Xiaoxin He, Xavier Bresson, Thomas Laurent, Bryan Hooi:
Explanations as Features: LLM-Based Features for Text-Attributed Graphs. CoRR abs/2305.19523 (2023) - [i80]Yuwen Li, Miao Xiong, Bryan Hooi:
GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning Benchmarks. CoRR abs/2306.00015 (2023) - [i79]Miao Xiong, Ailin Deng, Pang Wei Koh, Jiaying Wu, Shen Li, Jianqing Xu, Bryan Hooi:
Proximity-Informed Calibration for Deep Neural Networks. CoRR abs/2306.04590 (2023) - [i78]Xu Liu, Yutong Xia, Yuxuan Liang, Junfeng Hu, Yiwei Wang, Lei Bai, Chao Huang, Zhenguang Liu, Bryan Hooi, Roger Zimmermann:
LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting. CoRR abs/2306.08259 (2023) - [i77]Zhiyuan Hu, Chumin Liu, Yue Feng, Bryan Hooi:
PoetryDiffusion: Towards Joint Semantic and Metrical Manipulation in Poetry Generation. CoRR abs/2306.08456 (2023) - [i76]Zhiyuan Hu, Yue Feng, Anh Tuan Luu, Bryan Hooi, Aldo Lipani:
Unlocking the Potential of User Feedback: Leveraging Large Language Model as User Simulator to Enhance Dialogue System. CoRR abs/2306.09821 (2023) - [i75]Miao Xiong, Zhiyuan Hu, Xinyang Lu, Yifei Li, Jie Fu, Junxian He, Bryan Hooi:
Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs. CoRR abs/2306.13063 (2023) - [i74]Jiaying Wu, Bryan Hooi:
DECOR: Degree-Corrected Social Graph Refinement for Fake News Detection. CoRR abs/2307.00077 (2023) - [i73]Yuexin Li, Bryan Hooi:
Prompt-Based Zero- and Few-Shot Node Classification: A Multimodal Approach. CoRR abs/2307.11572 (2023) - [i72]Zemin Liu, Yuan Li, Nan Chen, Qian Wang, Bryan Hooi, Bingsheng He:
A Survey of Imbalanced Learning on Graphs: Problems, Techniques, and Future Directions. CoRR abs/2308.13821 (2023) - [i71]Zhiyuan Hu, Yue Feng, Yang Deng, Zekun Li, See-Kiong Ng, Anh Tuan Luu, Bryan Hooi:
Enhancing Large Language Model Induced Task-Oriented Dialogue Systems Through Look-Forward Motivated Goals. CoRR abs/2309.08949 (2023) - [i70]Jiaying Wu, Shen Li, Ailin Deng, Miao Xiong, Bryan Hooi:
Prompt-and-Align: Prompt-Based Social Alignment for Few-Shot Fake News Detection. CoRR abs/2309.16424 (2023) - [i69]Jintian Zhang, Xin Xu, Ningyu Zhang, Ruibo Liu, Bryan Hooi, Shumin Deng:
Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology View. CoRR abs/2310.02124 (2023) - [i68]Minji Yoon, Jing Yu Koh, Bryan Hooi, Ruslan Salakhutdinov:
Multimodal Graph Learning for Generative Tasks. CoRR abs/2310.07478 (2023) - [i67]Xu Liu, Junfeng Hu, Yuan Li, Shizhe Diao, Yuxuan Liang, Bryan Hooi, Roger Zimmermann:
UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecasting. CoRR abs/2310.09751 (2023) - [i66]Jiaying Wu, Bryan Hooi:
Fake News in Sheep's Clothing: Robust Fake News Detection Against LLM-Empowered Style Attacks. CoRR abs/2310.10830 (2023) - [i65]Yiwei Wang, Yujun Cai, Muhao Chen, Yuxuan Liang, Bryan Hooi:
Primacy Effect of ChatGPT. CoRR abs/2310.13206 (2023) - [i64]Jun Hu, Bryan Hooi, Bingsheng He:
Efficient Heterogeneous Graph Learning via Random Projection. CoRR abs/2310.14481 (2023) - [i63]Shumin Deng, Ningyu Zhang, Nay Oo, Bryan Hooi:
Towards A Unified View of Answer Calibration for Multi-Step Reasoning. CoRR abs/2311.09101 (2023) - [i62]Yifan Zhang, Bryan Hooi:
HiPA: Enabling One-Step Text-to-Image Diffusion Models via High-Frequency-Promoting Adaptation. CoRR abs/2311.18158 (2023) - 2022
- [j10]Minji Yoon, Théophile Gervet, Bryan Hooi, Christos Faloutsos:
Autonomous graph mining algorithm search with best performance trade-off. Knowl. Inf. Syst. 64(6): 1571-1602 (2022) - [j9]Jiaxin Jiang, Yuan Li, Bingsheng He, Bryan Hooi, Jia Chen, Johan Kok Zhi Kang:
Spade: A Real-Time Fraud Detection Framework on Evolving Graphs. Proc. VLDB Endow. 16(3): 461-469 (2022) - [j8]Siddharth Bhatia, Rui Liu, Bryan Hooi, Minji Yoon, Kijung Shin, Christos Faloutsos:
Real-Time Anomaly Detection in Edge Streams. ACM Trans. Knowl. Discov. Data 16(4): 75:1-75:22 (2022) - [j7]Miao Xiong, Shen Li, Wenjie Feng, Ailin Deng, Jihai Zhang, Bryan Hooi:
Birds of a Feather Trust Together: Knowing When to Trust a Classifier via Adaptive Neighborhood Aggregation. Trans. Mach. Learn. Res. 2022 (2022) - [c80]Adam Goodge, Bryan Hooi, See-Kiong Ng, Wee Siong Ng:
LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks. AAAI 2022: 6737-6745 - [c79]Aashish Kolluri, Teodora Baluta, Bryan Hooi, Prateek Saxena:
LPGNet: Link Private Graph Networks for Node Classification. CCS 2022: 1813-1827 - [c78]Ailin Deng, Shen Li, Miao Xiong, Zhirui Chen, Bryan Hooi:
Trust, but Verify: Using Self-supervised Probing to Improve Trustworthiness. ECCV (13) 2022: 361-377 - [c77]Adrien Benamira, Thomas Peyrin, Bryan Hooi Kuen-Yew:
Truth-Table Net: A New Convolutional Architecture Encodable by Design into SAT Formulas. ECCV Workshops (1) 2022: 483-500 - [c76]Xu Liu, Yuxuan Liang, Chao Huang, Yu Zheng, Bryan Hooi, Roger Zimmermann:
When do contrastive learning signals help spatio-temporal graph forecasting? SIGSPATIAL/GIS 2022: 5:1-5:12 - [c75]Kaixin Wang, Navdeep Kumar, Kuangqi Zhou, Bryan Hooi, Jiashi Feng, Shie Mannor:
The Geometry of Robust Value Functions. ICML 2022: 22727-22751 - [c74]Ailin Deng, Adam Goodge, Lang Yi Ang, Bryan Hooi:
CADET: Calibrated Anomaly Detection for Mitigating Hardness Bias. IJCAI 2022: 2002-2008 - [c73]Shen Li, Bryan Hooi:
Neural PCA for Flow-Based Representation Learning. IJCAI 2022: 3229-3235 - [c72]Yiwei Wang, Yujun Cai, Yuxuan Liang, Henghui Ding, Changhu Wang, Bryan Hooi:
Time-Aware Neighbor Sampling on Temporal Graphs. IJCNN 2022: 1-8 - [c71]Yiwei Wang, Bryan Hooi, Yozen Liu, Tong Zhao, Zhichun Guo, Neil Shah:
Flashlight: Scalable Link Prediction With Effective Decoders. LoG 2022: 14 - [c70]Kuangqi Zhou, Kaixin Wang, Jian Tang, Jiashi Feng, Bryan Hooi, Peilin Zhao, Tingyang Xu, Xinchao Wang:
Jointly Modelling Uncertainty and Diversity for Active Molecular Property Prediction. LoG 2022: 29 - [c69]Juncheng Liu, Zequn Sun, Bryan Hooi, Yiwei Wang, Dayiheng Liu, Baosong Yang, Xiaokui Xiao, Muhao Chen:
Dangling-Aware Entity Alignment with Mixed High-Order Proximities. NAACL-HLT (Findings) 2022: 1172-1184 - [c68]Yiwei Wang, Muhao Chen, Wenxuan Zhou, Yujun Cai, Yuxuan Liang, Bryan Hooi:
GraphCache: Message Passing as Caching for Sentence-Level Relation Extraction. NAACL-HLT (Findings) 2022: 1698-1708 - [c67]Yiwei Wang, Muhao Chen, Wenxuan Zhou, Yujun Cai, Yuxuan Liang, Dayiheng Liu, Baosong Yang, Juncheng Liu, Bryan Hooi:
Should We Rely on Entity Mentions for Relation Extraction? Debiasing Relation Extraction with Counterfactual Analysis. NAACL-HLT 2022: 3071-3081 - [c66]Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Xiaokui Xiao:
MGNNI: Multiscale Graph Neural Networks with Implicit Layers. NeurIPS 2022 - [c65]Yifan Zhang, Bryan Hooi, Lanqing Hong, Jiashi Feng:
Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition. NeurIPS 2022 - [c64]Juncheng Liu, Yiwei Wang, Bryan Hooi, Renchi Yang, Xiaokui Xiao:
LSCALE: Latent Space Clustering-Based Active Learning for Node Classification. ECML/PKDD (1) 2022: 55-70 - [c63]Adam Goodge, Bryan Hooi, See-Kiong Ng, Wee Siong Ng:
ARES: Locally Adaptive Reconstruction-Based Anomaly Scoring. ECML/PKDD (1) 2022: 193-208 - [c62]Jiaying Wu, Bryan Hooi:
Probing Spurious Correlations in Popular Event-Based Rumor Detection Benchmarks. ECML/PKDD (2) 2022: 274-290 - [c61]Nicholas Lim, Bryan Hooi, See-Kiong Ng, Yong Liang Goh, Renrong Weng, Rui Tan:
Hierarchical Multi-Task Graph Recurrent Network for Next POI Recommendation. SIGIR 2022: 1133-1143 - [c60]Xiaobing Sun, Wenjie Feng, Shenghua Liu, Yuyang Xie, Siddharth Bhatia, Bryan Hooi, Wenhan Wang, Xueqi Cheng:
MonLAD: Money Laundering Agents Detection in Transaction Streams. WSDM 2022: 976-986 - [c59]Siddharth Bhatia, Arjit Jain, Shivin Srivastava, Kenji Kawaguchi, Bryan Hooi:
MemStream: Memory-Based Streaming Anomaly Detection. WWW 2022: 610-621 - [i61]Xiaobing Sun, Wenjie Feng, Shenghua Liu, Yuyang Xie, Siddharth Bhatia, Bryan Hooi, Wenhan Wang, Xueqi Cheng:
MonLAD: Money Laundering Agents Detection in Transaction Streams. CoRR abs/2201.10051 (2022) - [i60]Kaixin Wang, Navdeep Kumar, Kuangqi Zhou, Bryan Hooi, Jiashi Feng, Shie Mannor:
The Geometry of Robust Value Functions. CoRR abs/2201.12929 (2022) - [i59]Juncheng Liu, Kenji Kawaguchi, Bryan Hooi, Yiwei Wang, Xiaokui Xiao:
EIGNN: Efficient Infinite-Depth Graph Neural Networks. CoRR abs/2202.10720 (2022) - [i58]Juncheng Liu, Zequn Sun, Bryan Hooi, Yiwei Wang, Dayiheng Liu, Baosong Yang, Xiaokui Xiao, Muhao Chen:
Dangling-Aware Entity Alignment with Mixed High-Order Proximities. CoRR abs/2205.02406 (2022) - [i57]Aashish Kolluri, Teodora Baluta, Bryan Hooi, Prateek Saxena:
LPGNet: Link Private Graph Networks for Node Classification. CoRR abs/2205.03105 (2022) - [i56]Yiwei Wang, Muhao Chen, Wenxuan Zhou, Yujun Cai, Yuxuan Liang, Dayiheng Liu, Baosong Yang, Juncheng Liu, Bryan Hooi:
Should We Rely on Entity Mentions for Relation Extraction? Debiasing Relation Extraction with Counterfactual Analysis. CoRR abs/2205.03784 (2022) - [i55]Yiwei Wang, Muhao Chen, Wenxuan Zhou, Yujun Cai, Yuxuan Liang, Bryan Hooi:
GRAPHCACHE: Message Passing as Caching for Sentence-Level Relation Extraction. CoRR abs/2205.03786 (2022) - [i54]Adam Goodge, Bryan Hooi, See-Kiong Ng, Wee Siong Ng:
ARES: Locally Adaptive Reconstruction-based Anomaly Scoring. CoRR abs/2206.07604 (2022) - [i53]Adrien Benamira, Thomas Peyrin, Bryan Hooi Kuen-Yew:
Truth-Table Net: A New Convolutional Architecture Encodable By Design Into SAT Formulas. CoRR abs/2208.08609 (2022) - [i52]Shen Li, Bryan Hooi:
Neural PCA for Flow-Based Representation Learning. CoRR abs/2208.10753 (2022) - [i51]Jiaying Wu, Bryan Hooi:
Probing Spurious Correlations in Popular Event-Based Rumor Detection Benchmarks. CoRR abs/2209.08799 (2022) - [i50]Yiwei Wang, Bryan Hooi, Yozen Liu, Tong Zhao, Zhichun Guo, Neil Shah:
Flashlight: Scalable Link Prediction with Effective Decoders. CoRR abs/2209.10100 (2022) - [i49]Nicholas Lim, Bryan Hooi, See-Kiong Ng, Yong Liang Goh:
Joint Triplet Loss Learning for Next New POI Recommendation. CoRR abs/2209.12162 (2022) - [i48]Shumin Deng, Chengming Wang, Zhoubo Li, Ningyu Zhang, Zelin Dai, Hehong Chen, Feiyu Xiong, Ming Yan, Qiang Chen, Mosha Chen, Jiaoyan Chen, Jeff Z. Pan, Bryan Hooi, Huajun Chen:
Construction and Applications of Billion-Scale Pre-trained Multimodal Business Knowledge Graph. CoRR abs/2209.15214 (2022) - [i47]Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Xiaokui Xiao:
MGNNI: Multiscale Graph Neural Networks with Implicit Layers. CoRR abs/2210.08353 (2022) - [i46]Kaixin Wang, Kuangqi Zhou, Jiashi Feng, Bryan Hooi, Xinchao Wang:
Reachability-Aware Laplacian Representation in Reinforcement Learning. CoRR abs/2210.13153 (2022) - [i45]Jiaxin Jiang, Yuan Li, Bingsheng He, Bryan Hooi, Jia Chen, Johan Kok Zhi Kang:
Spade: A Real-Time Fraud Detection Framework on Evolving Graphs (Complete Version). CoRR abs/2211.06977 (2022) - [i44]Yifan Zhang, Daquan Zhou, Bryan Hooi, Kai Wang, Jiashi Feng:
Expanding Small-Scale Datasets with Guided Imagination. CoRR abs/2211.13976 (2022) - [i43]Miao Xiong, Shen Li, Wenjie Feng, Ailin Deng, Jihai Zhang, Bryan Hooi:
Birds of a Feather Trust Together: Knowing When to Trust a Classifier via Adaptive Neighborhood Aggregation. CoRR abs/2211.16466 (2022) - [i42]Xiaoxin He, Bryan Hooi, Thomas Laurent, Adam Perold, Yann LeCun, Xavier Bresson:
A Generalization of ViT/MLP-Mixer to Graphs. CoRR abs/2212.13350 (2022) - 2021
- [j6]Wenjie Feng, Shenghua Liu, Christos Faloutsos, Bryan Hooi, Huawei Shen, Xueqi Cheng:
EagleMine: Vision-guided Micro-clusters recognition and collective anomaly detection. Future Gener. Comput. Syst. 115: 236-250 (2021) - [c58]Ailin Deng, Bryan Hooi:
Graph Neural Network-Based Anomaly Detection in Multivariate Time Series. AAAI 2021: 4027-4035 - [c57]Siddharth Bhatia, Arjit Jain, Bryan Hooi:
ExGAN: Adversarial Generation of Extreme Samples. AAAI 2021: 6750-6758 - [c56]Kuangqi Zhou, Yanfei Dong, Kaixin Wang, Wee Sun Lee, Bryan Hooi, Huan Xu, Jiashi Feng:
Understanding and Resolving Performance Degradation in Deep Graph Convolutional Networks. CIKM 2021: 2728-2737 - [c55]Hansheng Ren, Miao Xiong, Bryan Hooi:
Robust and Task-Aware Training of Deep Residual Networks for Varying-Lead ECG Classification. CinC 2021: 1-4 - [c54]Shen Li, Jianqing Xu, Xiaqing Xu, Pengcheng Shen, Shaoxin Li, Bryan Hooi:
Spherical Confidence Learning for Face Recognition. CVPR 2021: 15629-15637 - [c53]Kaixin Wang, Kuangqi Zhou, Qixin Zhang, Jie Shao, Bryan Hooi, Jiashi Feng:
Towards Better Laplacian Representation in Reinforcement Learning with Generalized Graph Drawing. ICML 2021: 11003-11012 - [c52]Siddharth Bhatia, Bryan Hooi, Leman Akoglu, Sourav Chatterjee, Xiaodong Jiang, Manish Gupta:
ODD: Outlier Detection and Description. KDD 2021: 4108-4109 - [c51]Yiwei Wang, Yujun Cai, Yuxuan Liang, Henghui Ding, Changhu Wang, Siddharth Bhatia, Bryan Hooi:
Adaptive Data Augmentation on Temporal Graphs. NeurIPS 2021: 1440-1452 - [c50]Koki Kawabata, Siddharth Bhatia, Rui Liu, Mohit Wadhwa, Bryan Hooi:
SSMF: Shifting Seasonal Matrix Factorization. NeurIPS 2021: 3863-3873 - [c49]Juncheng Liu, Kenji Kawaguchi, Bryan Hooi, Yiwei Wang, Xiaokui Xiao:
EIGNN: Efficient Infinite-Depth Graph Neural Networks. NeurIPS 2021: 18762-18773 - [c48]Yifan Zhang, Bryan Hooi, Dapeng Hu, Jian Liang, Jiashi Feng:
Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning. NeurIPS 2021: 29848-29860 - [c47]Siddharth Bhatia, Yiwei Wang, Bryan Hooi, Tanmoy Chakraborty:
GraphAnoGAN: Detecting Anomalous Snapshots from Attributed Graphs. ECML/PKDD (2) 2021: 36-51 - [c46]Shixuan Sun, Yuhang Chen, Bingsheng He, Bryan Hooi:
PathEnum: Towards Real-Time Hop-Constrained s-t Path Enumeration. SIGMOD Conference 2021: 1758-1770 - [c45]Nicholas Lim, Bryan Hooi, See-Kiong Ng, Xueou Wang, Yong Liang Goh, Renrong Weng, Rui Tan:
Origin-Aware Next Destination Recommendation with Personalized Preference Attention. WSDM 2021: 382-390 - [c44]Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Bryan Hooi:
CurGraph: Curriculum Learning for Graph Classification. WWW 2021: 1238-1248 - [c43]Siddharth Bhatia, Arjit Jain, Pan Li, Ritesh Kumar, Bryan Hooi:
MStream: Fast Anomaly Detection in Multi-Aspect Streams. WWW 2021: 3371-3382 - [c42]Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Bryan Hooi:
Mixup for Node and Graph Classification. WWW 2021: 3663-3674 - [i41]Yifan Zhang, Bryan Hooi, Dapeng Hu, Jian Liang, Jiashi Feng:
Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning. CoRR abs/2102.06605 (2021) - [i40]Shixuan Sun, Yuhang Chen, Bingsheng He, Bryan Hooi:
PathEnum: Towards Real-Time Hop-Constrained s-t Path Enumeration. CoRR abs/2103.11137 (2021) - [i39]Rui Liu, Siddharth Bhatia, Bryan Hooi:
Isconna: Streaming Anomaly Detection with Frequency and Patterns. CoRR abs/2104.01632 (2021) - [i38]Siddharth Bhatia, Arjit Jain, Shivin Srivastava, Kenji Kawaguchi, Bryan Hooi:
MemStream: Memory-Based Anomaly Detection in Multi-Aspect Streams with Concept Drift. CoRR abs/2106.03837 (2021) - [i37]Siddharth Bhatia, Mohit Wadhwa, Philip S. Yu, Bryan Hooi:
Sketch-Based Streaming Anomaly Detection in Dynamic Graphs. CoRR abs/2106.04486 (2021) - [i36]Ailin Deng, Bryan Hooi:
Graph Neural Network-Based Anomaly Detection in Multivariate Time Series. CoRR abs/2106.06947 (2021) - [i35]Siddharth Bhatia, Yiwei Wang, Bryan Hooi, Tanmoy Chakraborty:
GraphAnoGAN: Detecting Anomalous Snapshots from Attributed Graphs. CoRR abs/2106.15504 (2021) - [i34]Kaixin Wang, Kuangqi Zhou, Qixin Zhang, Jie Shao, Bryan Hooi, Jiashi Feng:
Towards Better Laplacian Representation in Reinforcement Learning with Generalized Graph Drawing. CoRR abs/2107.05545 (2021) - [i33]Yifan Zhang, Bryan Hooi, Lanqing Hong, Jiashi Feng:
Test-Agnostic Long-Tailed Recognition by Test-Time Aggregating Diverse Experts with Self-Supervision. CoRR abs/2107.09249 (2021) - [i32]Xu Liu, Yuxuan Liang, Yu Zheng, Bryan Hooi, Roger Zimmermann:
Spatio-Temporal Graph Contrastive Learning. CoRR abs/2108.11873 (2021) - [i31]Yifan Zhang, Bingyi Kang, Bryan Hooi, Shuicheng Yan, Jiashi Feng:
Deep Long-Tailed Learning: A Survey. CoRR abs/2110.04596 (2021) - [i30]Koki Kawabata, Siddharth Bhatia, Rui Liu, Mohit Wadhwa, Bryan Hooi:
SSMF: Shifting Seasonal Matrix Factorization. CoRR abs/2110.12763 (2021) - [i29]Shubhranshu Shekhar, Dhivya Eswaran, Bryan Hooi, Jonathan Elmer, Christos Faloutsos, Leman Akoglu:
Benefit-aware Early Prediction of Health Outcomes on Multivariate EEG Time Series. CoRR abs/2111.06032 (2021) - [i28]Yiwei Wang, Yujun Cai, Yuxuan Liang, Wei Wang, Henghui Ding, Muhao Chen, Jing Tang, Bryan Hooi:
Structure-Aware Label Smoothing for Graph Neural Networks. CoRR abs/2112.00499 (2021) - [i27]Shen Li, Jianqing Xu, Bryan Hooi:
Probabilistic Contrastive Loss for Self-Supervised Learning. CoRR abs/2112.01642 (2021) - [i26]Adam Goodge, Bryan Hooi, See-Kiong Ng, Wee Siong Ng:
LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks. CoRR abs/2112.05355 (2021) - [i25]Yiwei Wang, Yujun Cai, Yuxuan Liang, Henghui Ding, Changhu Wang, Bryan Hooi:
Time-Aware Neighbor Sampling for Temporal Graph Networks. CoRR abs/2112.09845 (2021) - 2020
- [j5]Kijung Shin, Sejoon Oh, Jisu Kim, Bryan Hooi, Christos Faloutsos:
Fast, Accurate and Provable Triangle Counting in Fully Dynamic Graph Streams. ACM Trans. Knowl. Discov. Data 14(2): 12:1-12:39 (2020) - [c41]Siddharth Bhatia, Bryan Hooi, Minji Yoon, Kijung Shin, Christos Faloutsos:
Midas: Microcluster-Based Detector of Anomalies in Edge Streams. AAAI 2020: 3242-3249 - [c40]Bryan Hooi, Kijung Shin, Hemank Lamba, Christos Faloutsos:
TellTail: Fast Scoring and Detection of Dense Subgraphs. AAAI 2020: 4150-4157 - [c39]Xiangfeng Li, Shenghua Liu, Zifeng Li, Xiaotian Han, Chuan Shi, Bryan Hooi, He Huang, Xueqi Cheng:
FlowScope: Spotting Money Laundering Based on Graphs. AAAI 2020: 4731-4738 - [c38]Nicholas Lim, Bryan Hooi, See-Kiong Ng, Xueou Wang, Yong Liang Goh, Renrong Weng, Jagannadan Varadarajan:
STP-UDGAT: Spatial-Temporal-Preference User Dimensional Graph Attention Network for Next POI Recommendation. CIKM 2020: 845-854 - [c37]Yiwei Wang, Shenghua Liu, Minji Yoon, Hemank Lamba, Wei Wang, Christos Faloutsos, Bryan Hooi:
Provably Robust Node Classification via Low-Pass Message Passing. ICDM 2020: 621-630 - [c36]Minji Yoon, Théophile Gervet, Bryan Hooi, Christos Faloutsos:
Autonomous Graph Mining Algorithm Search with Best Speed/Accuracy Trade-off. ICDM 2020: 751-760 - [c35]Shen Li, Bryan Hooi, Gim Hee Lee:
Identifying through Flows for Recovering Latent Representations. ICLR 2020 - [c34]Adam Goodge, Bryan Hooi, See-Kiong Ng, Wee Siong Ng:
Robustness of Autoencoders for Anomaly Detection Under Adversarial Impact. IJCAI 2020: 1244-1250 - [c33]Yiwei Wang, Wei Wang, Yujun Cai, Bryan Hooi, Beng Chin Ooi:
Detecting Implementation Bugs in Graph Convolutional Network based Node Classifiers. ISSRE 2020: 313-324 - [c32]Manh Tuan Do, Se-eun Yoon, Bryan Hooi, Kijung Shin:
Structural Patterns and Generative Models of Real-world Hypergraphs. KDD 2020: 176-186 - [c31]Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Juncheng Liu, Bryan Hooi:
NodeAug: Semi-Supervised Node Classification with Data Augmentation. KDD 2020: 207-217 - [c30]Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Bryan Hooi:
Progressive Supervision for Node Classification. ECML/PKDD (1) 2020: 266-281 - [i24]Wesley Joon-Wie Tann, Ee-Chien Chang, Bryan Hooi:
SHADOWCAST: Controlling Network Properties to Explain Graph Generation. CoRR abs/2006.03774 (2020) - [i23]Manh Tuan Do, Se-eun Yoon, Bryan Hooi, Kijung Shin:
Structural Patterns and Generative Models of Real-world Hypergraphs. CoRR abs/2006.07060 (2020) - [i22]Kuangqi Zhou, Yanfei Dong, Wee Sun Lee, Bryan Hooi, Huan Xu, Jiashi Feng:
Effective Training Strategies for Deep Graph Neural Networks. CoRR abs/2006.07107 (2020) - [i21]Siddharth Bhatia, Arjit Jain, Pan Li, Ritesh Kumar, Bryan Hooi:
MStream: Fast Streaming Multi-Aspect Group Anomaly Detection. CoRR abs/2009.08451 (2020) - [i20]Siddharth Bhatia, Rui Liu, Bryan Hooi, Minji Yoon, Kijung Shin, Christos Faloutsos:
Real-Time Streaming Anomaly Detection in Dynamic Graphs. CoRR abs/2009.08452 (2020) - [i19]Siddharth Bhatia, Arjit Jain, Bryan Hooi:
ExGAN: Adversarial Generation of Extreme Samples. CoRR abs/2009.08454 (2020) - [i18]Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Bryan Hooi:
GraphCrop: Subgraph Cropping for Graph Classification. CoRR abs/2009.10564 (2020) - [i17]Nicholas Lim, Bryan Hooi, See-Kiong Ng, Xueou Wang, Yong Liang Goh, Renrong Weng, Jagannadan Varadarajan:
STP-UDGAT: Spatial-Temporal-Preference User Dimensional Graph Attention Network for Next POI Recommendation. CoRR abs/2010.07024 (2020) - [i16]Minji Yoon, Bryan Hooi, Kijung Shin, Christos Faloutsos:
Fast and Accurate Anomaly Detection in Dynamic Graphs with a Two-Pronged Approach. CoRR abs/2011.13085 (2020) - [i15]Minji Yoon, Théophile Gervet, Bryan Hooi, Christos Faloutsos:
Autonomous Graph Mining Algorithm Search with Best Speed/Accuracy Trade-off. CoRR abs/2011.14925 (2020) - [i14]Nicholas Lim, Bryan Hooi, See-Kiong Ng, Xueou Wang, Yong Liang Goh, Renrong Weng, Rui Tan:
Origin-Aware Next Destination Recommendation with Personalized Preference Attention. CoRR abs/2012.01915 (2020) - [i13]Juncheng Liu, Yiwei Wang, Bryan Hooi, Renchi Yang, Xiaokui Xiao:
Active Learning for Node Classification: The Additional Learning Ability from Unlabelled Nodes. CoRR abs/2012.07065 (2020) - [i12]Shimiao Li, Amritanshu Pandey, Bryan Hooi, Christos Faloutsos, Larry T. Pileggi:
Dynamic Graph-Based Anomaly Detection in the Electrical Grid. CoRR abs/2012.15006 (2020)
2010 – 2019
- 2019
- [b1]Bryan Hooi:
Anomaly Detection in Graphs and Time Series: Algorithms and Applications. Carnegie Mellon University, USA, 2019 - [j4]Shenghua Liu, Bryan Hooi, Christos Faloutsos:
A Contrast Metric for Fraud Detection in Rich Graphs. IEEE Trans. Knowl. Data Eng. 31(12): 2235-2248 (2019) - [c29]Bin Zhou, Shenghua Liu, Bryan Hooi, Xueqi Cheng, Jing Ye:
BeatGAN: Anomalous Rhythm Detection using Adversarially Generated Time Series. IJCAI 2019: 4433-4439 - [c28]Minji Yoon, Bryan Hooi, Kijung Shin, Christos Faloutsos:
Fast and Accurate Anomaly Detection in Dynamic Graphs with a Two-Pronged Approach. KDD 2019: 647-657 - [c27]Wenjie Feng, Shenghua Liu, Christos Faloutsos, Bryan Hooi, Huawei Shen, Xueqi Cheng:
Beyond Outliers and on to Micro-clusters: Vision-Guided Anomaly Detection. PAKDD (1) 2019: 541-554 - [c26]Bryan Hooi, Christos Faloutsos:
Branch and Border: Partition-Based Change Detection in Multivariate Time Series. SDM 2019: 504-512 - [c25]Bryan Hooi, Kijung Shin, Shenghua Liu, Christos Faloutsos:
SMF: Drift-Aware Matrix Factorization with Seasonal Patterns. SDM 2019: 621-629 - [i11]Marko Jereminov, Bryan Hooi, Amritanshu Pandey, Hyun Ah Song, Christos Faloutsos, Lawrence T. Pileggi:
Impact of Load Models on Power Flow Optimization. CoRR abs/1902.04154 (2019) - [i10]Shen Li, Bryan Hooi, Gim Hee Lee:
Identifying through Flows for Recovering Latent Representations. CoRR abs/1909.12555 (2019) - [i9]Siddharth Bhatia, Bryan Hooi, Minji Yoon, Kijung Shin, Christos Faloutsos:
MIDAS: Microcluster-Based Detector of Anomalies in Edge Streams. CoRR abs/1911.04464 (2019) - 2018
- [j3]Kijung Shin, Bryan Hooi, Christos Faloutsos:
Fast, Accurate, and Flexible Algorithms for Dense Subtensor Mining. ACM Trans. Knowl. Discov. Data 12(3): 28:1-28:30 (2018) - [c24]Bryan Hooi, Leman Akoglu, Dhivya Eswaran, Amritanshu Pandey, Marko Jereminov, Larry T. Pileggi, Christos Faloutsos:
ChangeDAR: Online Localized Change Detection for Sensor Data on a Graph. CIKM 2018: 507-516 - [c23]Pudi Chen, Shenghua Liu, Chuan Shi, Bryan Hooi, Bai Wang, Xueqi Cheng:
NeuCast: Seasonal Neural Forecast of Power Grid Time Series. IJCAI 2018: 3315-3321 - [c22]Bryan Hooi, Dhivya Eswaran, Hyun Ah Song, Amritanshu Pandey, Marko Jereminov, Larry T. Pileggi, Christos Faloutsos:
GridWatch: Sensor Placement and Anomaly Detection in the Electrical Grid. ECML/PKDD (1) 2018: 71-86 - [c21]Aastha Nigam, Kijung Shin, Ashwin Bahulkar, Bryan Hooi, David Hachen, Boleslaw K. Szymanski, Christos Faloutsos, Nitesh V. Chawla:
ONE-M: Modeling the Co-evolution of Opinions and Network Connections. ECML/PKDD (2) 2018: 122-140 - [c20]Kijung Shin, Jisu Kim, Bryan Hooi, Christos Faloutsos:
Think Before You Discard: Accurate Triangle Counting in Graph Streams with Deletions. ECML/PKDD (2) 2018: 141-157 - [c19]Bryan Hooi, Hyun Ah Song, Amritanshu Pandey, Marko Jereminov, Larry T. Pileggi, Christos Faloutsos:
StreamCast: Fast and Online Mining of Power Grid Time Sequences. SDM 2018: 531-539 - [c18]Srijan Kumar, Bryan Hooi, Disha Makhija, Mohit Kumar, Christos Faloutsos, V. S. Subrahmanian:
REV2: Fraudulent User Prediction in Rating Platforms. WSDM 2018: 333-341 - [i8]Kijung Shin, Bryan Hooi, Jisu Kim, Christos Faloutsos:
Out-of-Core and Distributed Algorithms for Dense Subtensor Mining. CoRR abs/1802.01065 (2018) - 2017
- [j2]Bryan Hooi, Kijung Shin, Hyun Ah Song, Alex Beutel, Neil Shah, Christos Faloutsos:
Graph-Based Fraud Detection in the Face of Camouflage. ACM Trans. Knowl. Discov. Data 11(4): 44:1-44:26 (2017) - [c17]Shenghua Liu, Bryan Hooi, Christos Faloutsos:
HoloScope: Topology-and-Spike Aware Fraud Detection. CIKM 2017: 1539-1548 - [c16]Pedro Costa, Aurélio J. C. Campilho, Bryan Hooi, Asim Smailagic, Kris Kitani, Shenghua Liu, Christos Faloutsos, Adrian Galdran:
EyeQual: Accurate, Explainable, Retinal Image Quality Assessment. ICMLA 2017: 323-330 - [c15]Marko Jereminov, Amritanshu Pandey, Hyun Ah Song, Bryan Hooi, Christos Faloutsos, Larry T. Pileggi:
Linear load model for robust power system analysis. ISGT Europe 2017: 1-6 - [c14]Kijung Shin, Bryan Hooi, Jisu Kim, Christos Faloutsos:
DenseAlert: Incremental Dense-Subtensor Detection in Tensor Streams. KDD 2017: 1057-1066 - [c13]Bryan Hooi, Shenghua Liu, Asim Smailagic, Christos Faloutsos:
BeatLex: Summarizing and Forecasting Time Series with Patterns. ECML/PKDD (2) 2017: 3-19 - [c12]Hemank Lamba, Bryan Hooi, Kijung Shin, Christos Faloutsos, Jürgen Pfeffer:
zooRank: Ranking Suspicious Entities in Time-Evolving Tensors. ECML/PKDD (1) 2017: 68-84 - [c11]Hyun Ah Song, Bryan Hooi, Marko Jereminov, Amritanshu Pandey, Larry T. Pileggi, Christos Faloutsos:
PowerCast: Mining and Forecasting Power Grid Sequences. ECML/PKDD (2) 2017: 606-621 - [c10]Chi Ling Chan, Justin Lai, Bryan Hooi, Todd Davies:
The Message or the Messenger? Inferring Virality and Diffusion Structure from Online Petition Signature Data. SocInfo (1) 2017: 499-517 - [c9]Kijung Shin, Bryan Hooi, Jisu Kim, Christos Faloutsos:
D-Cube: Dense-Block Detection in Terabyte-Scale Tensors. WSDM 2017: 681-689 - [c8]Tsubasa Takahashi, Bryan Hooi, Christos Faloutsos:
AutoCyclone: Automatic Mining of Cyclic Online Activities with Robust Tensor Factorization. WWW 2017: 213-221 - [i7]Srijan Kumar, Bryan Hooi, Disha Makhija, Mohit Kumar, Christos Faloutsos, V. S. Subrahmanian:
FairJudge: Trustworthy User Prediction in Rating Platforms. CoRR abs/1703.10545 (2017) - [i6]Shenghua Liu, Bryan Hooi, Christos Faloutsos:
HoloScope: Topology-and-Spike Aware Fraud Detection. CoRR abs/1705.02505 (2017) - [i5]Kijung Shin, Bryan Hooi, Jisu Kim, Christos Faloutsos:
DenseAlert: Incremental Dense-Subtensor Detection in Tensor Streams. CoRR abs/1706.03374 (2017) - [i4]Chi Ling Chan, Justin Lai, Bryan Hooi, Todd Davies:
The Message or the Messenger? Inferring Virality and Diffusion Structure from Online Petition Signature Data. CoRR abs/1708.03472 (2017) - [i3]Wenjie Feng, Shenghua Liu, Christos Faloutsos, Bryan Hooi, Huawei Shen, Xueqi Cheng:
EagleMine: Vision-Guided Mining in Large Graphs. CoRR abs/1710.08756 (2017) - 2016
- [j1]Meng Jiang, Alex Beutel, Peng Cui, Bryan Hooi, Shiqiang Yang, Christos Faloutsos:
Spotting Suspicious Behaviors in Multimodal Data: A General Metric and Algorithms. IEEE Trans. Knowl. Data Eng. 28(8): 2187-2200 (2016) - [c7]Neil Shah, Alex Beutel, Bryan Hooi, Leman Akoglu, Stephan Günnemann, Disha Makhija, Mohit Kumar, Christos Faloutsos:
EdgeCentric: Anomaly Detection in Edge-Attributed Networks. ICDM Workshops 2016: 327-334 - [c6]Bryan Hooi, Hyun Ah Song, Alex Beutel, Neil Shah, Kijung Shin, Christos Faloutsos:
FRAUDAR: Bounding Graph Fraud in the Face of Camouflage. KDD 2016: 895-904 - [c5]Bryan Hooi, Hyun Ah Song, Evangelos E. Papalexakis, Rakesh Agrawal, Christos Faloutsos:
Matrices, Compression, Learning Curves: Formulation, and the GroupNteach Algorithms. PAKDD (2) 2016: 376-387 - [c4]Kijung Shin, Bryan Hooi, Christos Faloutsos:
M-Zoom: Fast Dense-Block Detection in Tensors with Quality Guarantees. ECML/PKDD (1) 2016: 264-280 - [c3]Bryan Hooi, Neil Shah, Alex Beutel, Stephan Günnemann, Leman Akoglu, Mohit Kumar, Disha Makhija, Christos Faloutsos:
BIRDNEST: Bayesian Inference for Ratings-Fraud Detection. SDM 2016: 495-503 - 2015
- [c2]Bryan Hooi, Hyun Ah Song, Evangelos E. Papalexakis, Rakesh Agrawal, Christos Faloutsos:
Education, Learning and Information Theory. ICDM Workshops 2015: 269-272 - [c1]Meng Jiang, Alex Beutel, Peng Cui, Bryan Hooi, Shiqiang Yang, Christos Faloutsos:
A General Suspiciousness Metric for Dense Blocks in Multimodal Data. ICDM 2015: 781-786 - [i2]Neil Shah, Alex Beutel, Bryan Hooi, Leman Akoglu, Stephan Günnemann, Disha Makhija, Mohit Kumar, Christos Faloutsos:
EdgeCentric: Anomaly Detection in Edge-Attributed Networks. CoRR abs/1510.05544 (2015) - [i1]Bryan Hooi, Neil Shah, Alex Beutel, Stephan Günnemann, Leman Akoglu, Mohit Kumar, Disha Makhija, Christos Faloutsos:
BIRDNEST: Bayesian Inference for Ratings-Fraud Detection. CoRR abs/1511.06030 (2015)
Coauthor Index
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