Bryan Hooi

Orcid: 0000-0002-5645-1754

According to our database1, Bryan Hooi authored at least 162 papers between 2015 and 2024.

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Bibliography

2024
CapMax: A Framework for Dynamic Network Representation Learning From the View of Multiuser Communication.
IEEE Trans. Neural Networks Learn. Syst., April, 2024

KnowPhish: Large Language Models Meet Multimodal Knowledge Graphs for Enhancing Reference-Based Phishing Detection.
CoRR, 2024

Seeing is Believing: Mitigating Hallucination in Large Vision-Language Models via CLIP-Guided Decoding.
CoRR, 2024

UniGraph: Learning a Cross-Domain Graph Foundation Model From Natural Language.
CoRR, 2024

Learning the Unlearned: Mitigating Feature Suppression in Contrastive Learning.
CoRR, 2024

G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering.
CoRR, 2024

Uncertainty of Thoughts: Uncertainty-Aware Planning Enhances Information Seeking in Large Language Models.
CoRR, 2024

PoetryDiffusion: Towards Joint Semantic and Metrical Manipulation in Poetry Generation.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Learning Hierarchical Spatial Tasks with Visiting Relations for Next POI Recommendation.
Trans. Recomm. Syst., December, 2023

Continuous-time graph directed information maximization for temporal network representation.
Inf. Sci., October, 2023

Deep Long-Tailed Learning: A Survey.
IEEE Trans. Pattern Anal. Mach. Intell., September, 2023

Time Series Anomaly Detection With Adversarial Reconstruction Networks.
IEEE Trans. Knowl. Data Eng., April, 2023

Benefit-aware early prediction of health outcomes on multivariate EEG time series.
J. Biomed. Informatics, March, 2023

A multi-scale reconstruction method for the anomaly detection in stochastic dynamic networks.
Neurocomputing, 2023

HiPA: Enabling One-Step Text-to-Image Diffusion Models via High-Frequency-Promoting Adaptation.
CoRR, 2023

Towards A Unified View of Answer Calibration for Multi-Step Reasoning.
CoRR, 2023

Efficient Heterogeneous Graph Learning via Random Projection.
CoRR, 2023

Fake News in Sheep's Clothing: Robust Fake News Detection Against LLM-Empowered Style Attacks.
CoRR, 2023

UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecasting.
CoRR, 2023

Multimodal Graph Learning for Generative Tasks.
CoRR, 2023

Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology View.
CoRR, 2023

Enhancing Large Language Model Induced Task-Oriented Dialogue Systems Through Look-Forward Motivated Goals.
CoRR, 2023

A Survey of Imbalanced Learning on Graphs: Problems, Techniques, and Future Directions.
CoRR, 2023

Prompt-Based Zero- and Few-Shot Node Classification: A Multimodal Approach.
CoRR, 2023

Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs.
CoRR, 2023

Unlocking the Potential of User Feedback: Leveraging Large Language Model as User Simulator to Enhance Dialogue System.
CoRR, 2023

PoetryDiffusion: Towards Joint Semantic and Metrical Manipulation in Poetry Generation.
CoRR, 2023

LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting.
CoRR, 2023

Proximity-Informed Calibration for Deep Neural Networks.
CoRR, 2023

Explanations as Features: LLM-Based Features for Text-Attributed Graphs.
CoRR, 2023

RETEXO: Scalable Neural Network Training over Distributed Graphs.
CoRR, 2023

Do We Really Need Graph Neural Networks for Traffic Forecasting?
CoRR, 2023

Graph Explicit Neural Networks: Explicitly Encoding Graphs for Efficient and Accurate Inference.
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Expanding Small-Scale Datasets with Guided Imagination.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Proximity-Informed Calibration for Deep Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

DECOR: Degree-Corrected Social Graph Refinement for Fake News Detection.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Sketch-Based Anomaly Detection in Streaming Graphs.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Towards Better Graph Representation Learning with Parameterized Decomposition & Filtering.
Proceedings of the International Conference on Machine Learning, 2023

Reachability-Aware Laplacian Representation in Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2023

GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning Benchmarks.
Proceedings of the International Conference on Machine Learning, 2023

A Generalization of ViT/MLP-Mixer to Graphs.
Proceedings of the International Conference on Machine Learning, 2023

Great Models Think Alike: Improving Model Reliability via Inter-Model Latent Agreement.
Proceedings of the International Conference on Machine Learning, 2023

Construction and Applications of Billion-Scale Pre-Trained Multimodal Business Knowledge Graph.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

TAP: A Comprehensive Data Repository for Traffic Accident Prediction in Road Networks.
Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems, 2023

Primacy Effect of ChatGPT.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Probabilistic Knowledge Distillation of Face Ensembles.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

How Fragile is Relation Extraction under Entity Replacements?
Proceedings of the 27th Conference on Computational Natural Language Learning, 2023

Prompt-and-Align: Prompt-Based Social Alignment for Few-Shot Fake News Detection.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Unlocking the Potential of User Feedback: Leveraging Large Language Model as User Simulators to Enhance Dialogue System.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

SPEECH: Structured Prediction with Energy-Based Event-Centric Hyperspheres.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
Birds of a Feather Trust Together: Knowing When to Trust a Classifier via Adaptive Neighborhood Aggregation.
Trans. Mach. Learn. Res., 2022

Real-Time Anomaly Detection in Edge Streams.
ACM Trans. Knowl. Discov. Data, 2022

Spade: A Real-Time Fraud Detection Framework on Evolving Graphs.
Proc. VLDB Endow., 2022

Autonomous graph mining algorithm search with best performance trade-off.
Knowl. Inf. Syst., 2022

Spade: A Real-Time Fraud Detection Framework on Evolving Graphs (Complete Version).
CoRR, 2022

Joint Triplet Loss Learning for Next New POI Recommendation.
CoRR, 2022

MemStream: Memory-Based Streaming Anomaly Detection.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

MonLAD: Money Laundering Agents Detection in Transaction Streams.
Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Hierarchical Multi-Task Graph Recurrent Network for Next POI Recommendation.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Probing Spurious Correlations in Popular Event-Based Rumor Detection Benchmarks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

LSCALE: Latent Space Clustering-Based Active Learning for Node Classification.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

ARES: Locally Adaptive Reconstruction-Based Anomaly Scoring.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

MGNNI: Multiscale Graph Neural Networks with Implicit Layers.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Should We Rely on Entity Mentions for Relation Extraction? Debiasing Relation Extraction with Counterfactual Analysis.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

GraphCache: Message Passing as Caching for Sentence-Level Relation Extraction.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

Dangling-Aware Entity Alignment with Mixed High-Order Proximities.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

Jointly Modelling Uncertainty and Diversity for Active Molecular Property Prediction.
Proceedings of the Learning on Graphs Conference, 2022

Flashlight: Scalable Link Prediction With Effective Decoders.
Proceedings of the Learning on Graphs Conference, 2022

Time-Aware Neighbor Sampling on Temporal Graphs.
Proceedings of the International Joint Conference on Neural Networks, 2022

Neural PCA for Flow-Based Representation Learning.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

CADET: Calibrated Anomaly Detection for Mitigating Hardness Bias.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

The Geometry of Robust Value Functions.
Proceedings of the International Conference on Machine Learning, 2022

When do contrastive learning signals help spatio-temporal graph forecasting?
Proceedings of the 30th International Conference on Advances in Geographic Information Systems, 2022

Trust, but Verify: Using Self-supervised Probing to Improve Trustworthiness.
Proceedings of the Computer Vision - ECCV 2022, 2022

LPGNet: Link Private Graph Networks for Node Classification.
Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022

LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
EagleMine: Vision-guided Micro-clusters recognition and collective anomaly detection.
Future Gener. Comput. Syst., 2021

Time-Aware Neighbor Sampling for Temporal Graph Networks.
CoRR, 2021

Probabilistic Contrastive Loss for Self-Supervised Learning.
CoRR, 2021

Structure-Aware Label Smoothing for Graph Neural Networks.
CoRR, 2021

Spatio-Temporal Graph Contrastive Learning.
CoRR, 2021

Test-Agnostic Long-Tailed Recognition by Test-Time Aggregating Diverse Experts with Self-Supervision.
CoRR, 2021

Sketch-Based Streaming Anomaly Detection in Dynamic Graphs.
CoRR, 2021

MemStream: Memory-Based Anomaly Detection in Multi-Aspect Streams with Concept Drift.
CoRR, 2021

Isconna: Streaming Anomaly Detection with Frequency and Patterns.
CoRR, 2021

Mixup for Node and Graph Classification.
Proceedings of the WWW '21: The Web Conference 2021, 2021

CurGraph: Curriculum Learning for Graph Classification.
Proceedings of the WWW '21: The Web Conference 2021, 2021

MStream: Fast Anomaly Detection in Multi-Aspect Streams.
Proceedings of the WWW '21: The Web Conference 2021, 2021

Origin-Aware Next Destination Recommendation with Personalized Preference Attention.
Proceedings of the WSDM '21, 2021

PathEnum: Towards Real-Time Hop-Constrained s-t Path Enumeration.
Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

GraphAnoGAN: Detecting Anomalous Snapshots from Attributed Graphs.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Adaptive Data Augmentation on Temporal Graphs.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

EIGNN: Efficient Infinite-Depth Graph Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

SSMF: Shifting Seasonal Matrix Factorization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

ODD: Outlier Detection and Description.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Towards Better Laplacian Representation in Reinforcement Learning with Generalized Graph Drawing.
Proceedings of the 38th International Conference on Machine Learning, 2021

Spherical Confidence Learning for Face Recognition.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Robust and Task-Aware Training of Deep Residual Networks for Varying-Lead ECG Classification.
Proceedings of the Computing in Cardiology, CinC 2021, Brno, 2021

Understanding and Resolving Performance Degradation in Deep Graph Convolutional Networks.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Graph Neural Network-Based Anomaly Detection in Multivariate Time Series.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

ExGAN: Adversarial Generation of Extreme Samples.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Fast, Accurate and Provable Triangle Counting in Fully Dynamic Graph Streams.
ACM Trans. Knowl. Discov. Data, 2020

Dynamic Graph-Based Anomaly Detection in the Electrical Grid.
CoRR, 2020

Active Learning for Node Classification: The Additional Learning Ability from Unlabelled Nodes.
CoRR, 2020

GraphCrop: Subgraph Cropping for Graph Classification.
CoRR, 2020

Real-Time Streaming Anomaly Detection in Dynamic Graphs.
CoRR, 2020

MStream: Fast Streaming Multi-Aspect Group Anomaly Detection.
CoRR, 2020

Effective Training Strategies for Deep Graph Neural Networks.
CoRR, 2020

SHADOWCAST: Controlling Network Properties to Explain Graph Generation.
CoRR, 2020

Progressive Supervision for Node Classification.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

NodeAug: Semi-Supervised Node Classification with Data Augmentation.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Structural Patterns and Generative Models of Real-world Hypergraphs.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Detecting Implementation Bugs in Graph Convolutional Network based Node Classifiers.
Proceedings of the 31st IEEE International Symposium on Software Reliability Engineering, 2020

Robustness of Autoencoders for Anomaly Detection Under Adversarial Impact.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Identifying through Flows for Recovering Latent Representations.
Proceedings of the 8th International Conference on Learning Representations, 2020

Autonomous Graph Mining Algorithm Search with Best Speed/Accuracy Trade-off.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Provably Robust Node Classification via Low-Pass Message Passing.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

STP-UDGAT: Spatial-Temporal-Preference User Dimensional Graph Attention Network for Next POI Recommendation.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

FlowScope: Spotting Money Laundering Based on Graphs.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

TellTail: Fast Scoring and Detection of Dense Subgraphs.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Midas: Microcluster-Based Detector of Anomalies in Edge Streams.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Anomaly Detection in Graphs and Time Series: Algorithms and Applications.
PhD thesis, 2019

A Contrast Metric for Fraud Detection in Rich Graphs.
IEEE Trans. Knowl. Data Eng., 2019

Impact of Load Models on Power Flow Optimization.
CoRR, 2019

SMF: Drift-Aware Matrix Factorization with Seasonal Patterns.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Branch and Border: Partition-Based Change Detection in Multivariate Time Series.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Beyond Outliers and on to Micro-clusters: Vision-Guided Anomaly Detection.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

Fast and Accurate Anomaly Detection in Dynamic Graphs with a Two-Pronged Approach.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

BeatGAN: Anomalous Rhythm Detection using Adversarially Generated Time Series.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018
Fast, Accurate, and Flexible Algorithms for Dense Subtensor Mining.
ACM Trans. Knowl. Discov. Data, 2018

Out-of-Core and Distributed Algorithms for Dense Subtensor Mining.
CoRR, 2018

REV2: Fraudulent User Prediction in Rating Platforms.
Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, 2018

StreamCast: Fast and Online Mining of Power Grid Time Sequences.
Proceedings of the 2018 SIAM International Conference on Data Mining, 2018

Think Before You Discard: Accurate Triangle Counting in Graph Streams with Deletions.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

ONE-M: Modeling the Co-evolution of Opinions and Network Connections.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

GridWatch: Sensor Placement and Anomaly Detection in the Electrical Grid.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

NeuCast: Seasonal Neural Forecast of Power Grid Time Series.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

ChangeDAR: Online Localized Change Detection for Sensor Data on a Graph.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

2017
Graph-Based Fraud Detection in the Face of Camouflage.
ACM Trans. Knowl. Discov. Data, 2017

EagleMine: Vision-Guided Mining in Large Graphs.
CoRR, 2017

FairJudge: Trustworthy User Prediction in Rating Platforms.
CoRR, 2017

AutoCyclone: Automatic Mining of Cyclic Online Activities with Robust Tensor Factorization.
Proceedings of the 26th International Conference on World Wide Web, 2017

D-Cube: Dense-Block Detection in Terabyte-Scale Tensors.
Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, 2017

The Message or the Messenger? Inferring Virality and Diffusion Structure from Online Petition Signature Data.
Proceedings of the Social Informatics, 2017

PowerCast: Mining and Forecasting Power Grid Sequences.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

zooRank: Ranking Suspicious Entities in Time-Evolving Tensors.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

BeatLex: Summarizing and Forecasting Time Series with Patterns.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

DenseAlert: Incremental Dense-Subtensor Detection in Tensor Streams.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Linear load model for robust power system analysis.
Proceedings of the 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, 2017

EyeQual: Accurate, Explainable, Retinal Image Quality Assessment.
Proceedings of the 16th IEEE International Conference on Machine Learning and Applications, 2017

HoloScope: Topology-and-Spike Aware Fraud Detection.
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

2016
Spotting Suspicious Behaviors in Multimodal Data: A General Metric and Algorithms.
IEEE Trans. Knowl. Data Eng., 2016

BIRDNEST: Bayesian Inference for Ratings-Fraud Detection.
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

M-Zoom: Fast Dense-Block Detection in Tensors with Quality Guarantees.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

Matrices, Compression, Learning Curves: Formulation, and the GroupNteach Algorithms.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2016

FRAUDAR: Bounding Graph Fraud in the Face of Camouflage.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

EdgeCentric: Anomaly Detection in Edge-Attributed Networks.
Proceedings of the IEEE International Conference on Data Mining Workshops, 2016

2015
A General Suspiciousness Metric for Dense Blocks in Multimodal Data.
Proceedings of the 2015 IEEE International Conference on Data Mining, 2015

Education, Learning and Information Theory.
Proceedings of the IEEE International Conference on Data Mining Workshop, 2015


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