Carl Yang

Orcid: 0000-0001-9145-4531

Affiliations:
  • Emory University, Department of Computer Science, Atlanta, GA, USA
  • University of Illinois at Urbana-Champaign, Urbana, IL, USA (PhD 2020)


According to our database1, Carl Yang authored at least 172 papers between 2017 and 2024.

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Bibliography

2024
Automatic Hypergraph Generation for Enhancing Recommendation With Sparse Optimization.
IEEE Trans. Multim., 2024

A simple but tough-to-beat baseline for fMRI time-series classification.
NeuroImage, 2024

SimRAG: Self-Improving Retrieval-Augmented Generation for Adapting Large Language Models to Specialized Domains.
CoRR, 2024

Attack as Defense: Run-time Backdoor Implantation for Image Content Protection.
CoRR, 2024

Measuring Spiritual Values and Bias of Large Language Models.
CoRR, 2024

Integrating Planning into Single-Turn Long-Form Text Generation.
CoRR, 2024

Boosting Reward Model with Preference-Conditional Multi-Aspect Synthetic Data Generation.
CoRR, 2024

GC-Bench: A Benchmark Framework for Graph Condensation with New Insights.
CoRR, 2024

A Pure Transformer Pretraining Framework on Text-attributed Graphs.
CoRR, 2024

Biomedical Visual Instruction Tuning with Clinician Preference Alignment.
CoRR, 2024

GuardAgent: Safeguard LLM Agents by a Guard Agent via Knowledge-Enabled Reasoning.
CoRR, 2024

From Basic to Extra Features: Hypergraph Transformer Pretrain-then-Finetuning for Balanced Clinical Predictions on EHR.
CoRR, 2024

Efficient Two-Stage Gaussian Process Regression Via Automatic Kernel Search and Subsampling.
CoRR, 2024

MedAdapter: Efficient Test-Time Adaptation of Large Language Models towards Medical Reasoning.
CoRR, 2024

BrainODE: Dynamic Brain Signal Analysis via Graph-Aided Neural Ordinary Differential Equations.
CoRR, 2024

LLMs-based Few-Shot Disease Predictions using EHR: A Novel Approach Combining Predictive Agent Reasoning and Critical Agent Instruction.
CoRR, 2024

CASPER: Causality-Aware Spatiotemporal Graph Neural Networks for Spatiotemporal Time Series Imputation.
CoRR, 2024

Multimodal Fusion of EHR in Structures and Semantics: Integrating Clinical Records and Notes with Hypergraph and LLM.
CoRR, 2024

MuseGraph: Graph-oriented Instruction Tuning of Large Language Models for Generic Graph Mining.
CoRR, 2024

Are Synthetic Time-series Data Really not as Good as Real Data?
CoRR, 2024

Evaluation of General Large Language Models in Contextually Assessing Semantic Concepts Extracted from Adult Critical Care Electronic Health Record Notes.
CoRR, 2024

Contrastive Unlearning: A Contrastive Approach to Machine Unlearning.
CoRR, 2024

EHRAgent: Code Empowers Large Language Models for Complex Tabular Reasoning on Electronic Health Records.
CoRR, 2024

Beyond Efficiency: A Systematic Survey of Resource-Efficient Large Language Models.
CoRR, 2024

DPAR: Decoupled Graph Neural Networks with Node-Level Differential Privacy.
Proceedings of the ACM on Web Conference 2024, 2024

Enhancing Progressive Diagnosis Prediction in Healthcare with Continuous Normalizing Flows.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

BoxCare: A Box Embedding Model for Disease Representation and Diagnosis Prediction in Healthcare Data.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Uncertainty-Aware Pre-Trained Foundation Models for Patient Risk Prediction via Gaussian Process.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction.
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

PromptLink: Leveraging Large Language Models for Cross-Source Biomedical Concept Linking.
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Deep Efficient Private Neighbor Generation for Subgraph Federated Learning.
Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

Helper Recommendation with seniority control in Online Health Community.
Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

Interpretable Spatio-Temporal Embedding for Brain Structural-Effective Network with Ordinary Differential Equation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

TACCO: Task-guided Co-clustering of Clinical Concepts and Patient Visits for Disease Subtyping based on EHR Data.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

FedKDD: International Joint Workshop on Federated Learning for Data Mining and Graph Analytics.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Representation Learning of Temporal Graphs with Structural Roles.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

ExpertODE: Continuous Diagnosis Prediction with Expert Enhanced Neural Ordinary Differential Equations.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2024

Logical Relation Modeling and Mining in Hyperbolic Space for Recommendation.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

EHRAgent: Code Empowers Large Language Models for Few-shot Complex Tabular Reasoning on Electronic Health Records.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

MedAdapter: Efficient Test-Time Adaptation of Large Language Models Towards Medical Reasoning.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

BMRetriever: Tuning Large Language Models as Better Biomedical Text Retrievers.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Federated Node Classification over Distributed Ego-Networks with Secure Contrastive Embedding Sharing.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

HypMix: Hyperbolic Representation Learning for Graphs with Mixed Hierarchical and Non-hierarchical Structures.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Causality-Aware Spatiotemporal Graph Neural Networks for Spatiotemporal Time Series Imputation.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

RAM-EHR: Retrieval Augmentation Meets Clinical Predictions on Electronic Health Records.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics, 2024

Knowledge-Infused Prompting: Assessing and Advancing Clinical Text Data Generation with Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

Unveiling Implicit Deceptive Patterns in Multi-Modal Fake News via Neuro-Symbolic Reasoning.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Weakly Supervised Concept Map Generation Through Task-Guided Graph Translation.
IEEE Trans. Knowl. Data Eng., October, 2023

Finding High-Quality Item Attributes for Recommendation.
IEEE Trans. Knowl. Data Eng., August, 2023

Adversarial Attack and Defense on Graph Data: A Survey.
IEEE Trans. Knowl. Data Eng., August, 2023

Motif-guided heterogeneous graph deep generation.
Knowl. Inf. Syst., July, 2023

GCN for HIN via Implicit Utilization of Attention and Meta-Paths.
IEEE Trans. Knowl. Data Eng., April, 2023

BrainGB: A Benchmark for Brain Network Analysis With Graph Neural Networks.
IEEE Trans. Medical Imaging, February, 2023

Cross-Modal Data Augmentation for Tasks of Different Modalities.
IEEE Trans. Multim., 2023

Knowledge-Infused Prompting: Assessing and Advancing Clinical Text Data Generation with Large Language Models.
CoRR, 2023

Evaluation and Mitigation of Agnosia in Multimodal Large Language Models.
CoRR, 2023

A Survey on Knowledge Graphs for Healthcare: Resources, Applications, and Promises.
CoRR, 2023

Beyond One-Model-Fits-All: A Survey of Domain Specialization for Large Language Models.
CoRR, 2023

Deep Graph Neural Networks via Flexible Subgraph Aggregation.
CoRR, 2023

Federated Node Classification over Graphs with Latent Link-type Heterogeneity.
Proceedings of the ACM Web Conference 2023, 2023

Weakly-Supervised Scientific Document Classification via Retrieval-Augmented Multi-Stage Training.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

HiPrompt: Few-Shot Biomedical Knowledge Fusion via Hierarchy-Oriented Prompting.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Better with Less: A Data-Active Perspective on Pre-Training Graph Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

WalkLM: A Uniform Language Model Fine-tuning Framework for Attributed Graph Embedding.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Open Visual Knowledge Extraction via Relation-Oriented Multimodality Model Prompting.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Contrastive Intra- and Inter-Modality Generation for Enhancing Incomplete Multimedia Recommendation.
Proceedings of the 31st ACM International Conference on Multimedia, 2023

FedAA: Using Non-sensitive Modalities to Improve Federated Learning while Preserving Image Privacy.
Proceedings of the 31st ACM International Conference on Multimedia, 2023

Graph-Aware Language Model Pre-Training on a Large Graph Corpus Can Help Multiple Graph Applications.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

R-Mixup: Riemannian Mixup for Biological Networks.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

When to Pre-Train Graph Neural Networks? From Data Generation Perspective!
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Deep Dag Learning of Effective Brain Connectivity for FMRI Analysis.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Transformer-Based Hierarchical Clustering for Brain Network Analysis.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Graph Neural Network Modeling of Web Search Activity for Real-time Pandemic Forecasting.
Proceedings of the 11th IEEE International Conference on Healthcare Informatics, 2023

Enhancing Personalized Healthcare via Capturing Disease Severity, Interaction, and Progression.
Proceedings of the IEEE International Conference on Data Mining, 2023

Revisiting Citation Prediction with Cluster-Aware Text-Enhanced Heterogeneous Graph Neural Networks.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Dynamic Activation of Clients and Parameters for Federated Learning over Heterogeneous Graphs.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

MuG: A Multimodal Classification Benchmark on Game Data with Tabular, Textual, and Visual Fields.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

PTGB: Pre-Train Graph Neural Networks for Brain Network Analysis.
Proceedings of the Conference on Health, Inference, and Learning, 2023

øurs: Mobile Sensing based Fluid Overload Detection for End Stage Kidney Disease Patients using _Sensor _Relation _Dual _Autoencoder.
Proceedings of the Conference on Health, Inference, and Learning, 2023

Dynamic Brain Transformer with Multi-Level Attention for Functional Brain Network Analysis.
Proceedings of the IEEE EMBS International Conference on Biomedical and Health Informatics, 2023

PV2TEA: Patching Visual Modality to Textual-Established Information Extraction.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

Neighborhood-Regularized Self-Training for Learning with Few Labels.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Heterogeneous Network Representation Learning: A Unified Framework With Survey and Benchmark.
IEEE Trans. Knowl. Data Eng., 2022

Graph Federated Learning with Hidden Representation Sharing.
CoRR, 2022

Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks.
CoRR, 2022

Towards Training Graph Neural Networks with Node-Level Differential Privacy.
CoRR, 2022

A Bird's-Eye Tutorial of Graph Attention Architectures.
CoRR, 2022

Partial Relaxed Optimal Transport for Denoised Recommendation.
CoRR, 2022

Shift-Robust Node Classification via Graph Adversarial Clustering.
CoRR, 2022

Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation.
CoRR, 2022

Exploiting Data Sparsity in Secure Cross-Platform Social Recommendation.
CoRR, 2022

KoMen: Domain Knowledge Guided Interaction Recommendation for Emerging Scenarios.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

MetaCare++: Meta-Learning with Hierarchical Subtyping for Cold-Start Diagnosis Prediction in Healthcare Data.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Structure-Enhanced Heterogeneous Graph Contrastive Learning.
Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

Brain Network Transformer.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

SAIS: Supervising and Augmenting Intermediate Steps for Document-Level Relation Extraction.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Counterfactual and Factual Reasoning over Hypergraphs for Interpretable Clinical Predictions on EHR.
Proceedings of the Machine Learning for Health, 2022

FBNETGEN: Task-aware GNN-based fMRI Analysis via Functional Brain Network Generation.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

Interpretable Graph Neural Networks for Connectome-Based Brain Disorder Analysis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Dynamic Network Anomaly Modeling of Cell-Phone Call Detail Records for Infectious Disease Surveillance.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Data-Efficient Brain Connectome Analysis via Multi-Task Meta-Learning.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

4SDrug: Symptom-based Set-to-set Small and Safe Drug Recommendation.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

BrainNet: Epileptic Wave Detection from SEEG with Hierarchical Graph Diffusion Learning.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Structure-Preserving Graph Kernel for Brain Network Classification.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

Data-Free Adversarial Knowledge Distillation for Graph Neural Networks.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Graph Auto-Encoder via Neighborhood Wasserstein Reconstruction.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Enhancing Recommendation with Automated Tag Taxonomy Construction in Hyperbolic Space.
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Efficient Federated Learning on Knowledge Graphs via Privacy-preserving Relation Embedding Aggregation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Joint Embedding of Structural and Functional Brain Networks with Graph Neural Networks for Mental Illness Diagnosis.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

How Can Graph Neural Networks Help Document Retrieval: A Case Study on CORD19 with Concept Map Generation.
Proceedings of the Advances in Information Retrieval, 2022

The 1st International Workshop on Federated Learning with Graph Data (FedGraph).
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Partial Relaxed Optimal Transport for Denoised Recommendation.
Proceedings of the Workshop on Deep Learning for Search and Recommendation (DL4SR 2022) co-located with the 31st ACM International Conference on Information and Knowledge Management (CIKM 2022), 2022

On Positional and Structural Node Features for Graph Neural Networks on Non-attributed Graphs.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Learning Task-Aware Effective Brain Connectivity for fMRI Analysis with Graph Neural Networks (Extended Abstract).
Proceedings of the IEEE International Conference on Big Data, 2022

Pre-train Graph Neural Networks for Brain Network Analysis (Extended Abstract).
Proceedings of the IEEE International Conference on Big Data, 2022

Transformer-Based Hierarchical Clustering for Brain Network Analysis (Extended Abstract).
Proceedings of the IEEE International Conference on Big Data, 2022

BrainGB: A Benchmark for Brain Network Analysis with Graph Neural Networks (Extended Abstract).
Proceedings of the IEEE International Conference on Big Data, 2022

Multi-View Brain Network Analysis with Cross-View Missing Network Generation.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

Open-World Taxonomy and Knowledge Graph Co-Learning.
Proceedings of the 4th Conference on Automated Knowledge Base Construction, 2022

2021
Structure-Aware Hard Negative Mining for Heterogeneous Graph Contrastive Learning.
CoRR, 2021

Effective and Interpretable fMRI Analysis via Functional Brain Network Generation.
CoRR, 2021

BrainNNExplainer: An Interpretable Graph Neural Network Framework for Brain Network based Disease Analysis.
CoRR, 2021

Controllable Gradient Item Retrieval.
Proceedings of the WWW '21: The Web Conference 2021, 2021

Learning and Updating Node Embedding on Dynamic Heterogeneous Information Network.
Proceedings of the WSDM '21, 2021

Time-Series Event Prediction with Evolutionary State Graph.
Proceedings of the WSDM '21, 2021

Zero-Shot Scene Graph Relation Prediction Through Commonsense Knowledge Integration.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Subgraph Federated Learning with Missing Neighbor Generation.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Federated Graph Classification over Non-IID Graphs.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Exploiting Data Sparsity in Secure Cross-Platform Social Recommendation.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

TAXOGAN: Hierarchical Network Representation Learning via Taxonomy Guided Generative Adversarial Networks (Extended Abstract).
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Secure Deep Graph Generation with Link Differential Privacy.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Graph Entropy Guided Node Embedding Dimension Selection for Graph Neural Networks.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Understanding Structural Vulnerability in Graph Convolutional Networks.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Deep Generation of Heterogeneous Networks.
Proceedings of the IEEE International Conference on Data Mining, 2021

Multi-Facet Recommender Networks with Spherical Optimization.
Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

Lightweight Visual Question Answering using Scene Graphs.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020
Multi-facet graph mining with contextualized projections
PhD thesis, 2020

Secure Network Release with Link Privacy.
CoRR, 2020

Heterogeneous Network Representation Learning: Survey, Benchmark, Evaluation, and Beyond.
CoRR, 2020

cube2net: Efficient Query-Specific Network Construction with Data Cube Organization.
CoRR, 2020

Relation Learning on Social Networks with Multi-Modal Graph Edge Variational Autoencoders.
Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

Neural Concept Map Generation for Effective Document Classification with Interpretable Structured Summarization.
Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Certifiable Robustness to Discrete Adversarial Perturbations for Factorization Machines.
Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

MultiSage: Empowering GCN with Contextualized Multi-Embeddings on Web-Scale Multipartite Networks.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Unsupervised Differentiable Multi-aspect Network Embedding.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

When Do GNNs Work: Understanding and Improving Neighborhood Aggregation.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Co-Embedding Network Nodes and Hierarchical Labels with Taxonomy Based Generative Adversarial Networks.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Integrating Group Homophily and Individual Personality of Topics Can Better Model Network Communities.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Graph Clustering with Embedding Propagation.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019
CubeNet: Multi-Facet Hierarchical Heterogeneous Network Construction, Analysis, and Mining.
CoRR, 2019

Place Deduplication with Embeddings.
Proceedings of the World Wide Web Conference, 2019

Relationship Profiling over Social Networks: Reverse Smoothness from Similarity to Closeness.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

User-Guided Clustering in Heterogeneous Information Networks via Motif-Based Comprehensive Transcription.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Conditional Structure Generation through Graph Variational Generative Adversarial Nets.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

RASE: Relationship Aware Social Embedding.
Proceedings of the International Joint Conference on Neural Networks, 2019

Neural Embedding Propagation on Heterogeneous Networks.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

cube2net: Efficient Query-Specific Network Construction with Data Cube Organization.
Proceedings of the 2019 International Conference on Data Mining Workshops, 2019

Query-Specific Knowledge Summarization with Entity Evolutionary Networks.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Non-local Attention Learning on Large Heterogeneous Information Networks.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018
Higher-Order Clustering in Heterogeneous Information Networks.
CoRR, 2018

mvn2vec: Preservation and Collaboration in Multi-View Network Embedding.
CoRR, 2018

Similarity Modeling on Heterogeneous Networks via Automatic Path Discovery.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

I Know You'll Be Back: Interpretable New User Clustering and Churn Prediction on a Mobile Social Application.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Meta-Graph Based HIN Spectral Embedding: Methods, Analyses, and Insights.
Proceedings of the IEEE International Conference on Data Mining, 2018

Did You Enjoy the Ride? Understanding Passenger Experience via Heterogeneous Network Embedding.
Proceedings of the 34th IEEE International Conference on Data Engineering, 2018

Node, Motif and Subgraph: Leveraging Network Functional Blocks Through Structural Convolution.
Proceedings of the IEEE/ACM 2018 International Conference on Advances in Social Networks Analysis and Mining, 2018

Spatiotemporal Activity Modeling Under Data Scarcity: A Graph-Regularized Cross-Modal Embedding Approach.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Graph Clustering with Dynamic Embedding.
CoRR, 2017

CONE: Community Oriented Network Embedding.
CoRR, 2017

Bi-directional Joint Inference for User Links and Attributes on Large Social Graphs.
Proceedings of the 26th International Conference on World Wide Web Companion, 2017

Bridging Collaborative Filtering and Semi-Supervised Learning: A Neural Approach for POI Recommendation.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017


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