Publication

Conference

D. Jin, Y. Gong, Z. Wang, Z. Yu, D. He, Y. Huang and W. Wang. Graph Neural Network for Higher-Order Dependency Networks. The Web Conference, 2022 (acceptance rate 17.7%).
D. He, R. Guo, X. Wang, D. Jin, Y. Huang and W. Wang. Inflation Improves Graph Learning. The Web Conference, 2022 (acceptance rate 17.7%).

T. Wang, R. Wang, D. Jin, D. He, Y. Huang. Powerful Graph Convolutional Networks with Adaptive Propagation Mechanism for Homophily and Heterophily. AAAI, 2022 (acceptance rate 15%)!
D. He, S. Li, D. Jin, P. Jiao and Y. Huang. Self-Guided Community Detection on Networks with Missing Edges. IJCAI, 2021 (acceptance rate 13.9%)!

H. Shan, D. Jin, P. Jiao, Z. Liu, B. Li, and Y. Huang. NF-VGA: Incorporating Normalizing Flows into Graph Variational Autoencoder for Embedding Attribute Networks. ICDM, 2020 (acceptance rate 19.7%)!
D. He, L. Zhai, Z. Li, L. Yang, D. Jin, Y. Huang, and P. Yu. Adversarial Mutual Information Learning for Network Embedding. IJCAI-PRICAI, 2020 (acceptance rate 12.6%).
Y. Huang. Improving Classification Accuracy by Mining Deterministic and Frequent Rules. FLAIRS, 2020.

D. He, W. Song, D. Jin, Z. Feng, and Y. Huang. An End-to-End Community Detection Model: Integrating LDA into Markov Random Field via Factor Graph. IJCAI, 2019 (acceptance rate 14%).
D. Jin. J. Huang, P. Jiao, L. Yang, D. He, F. Fogelman, and Y. Huang. A Novel Generative Topic Embedding Model by Introducing Network Communities. WWW, 2019 (acceptance rate 20%).

Y. Huang. Causal Inference from Time Series Data. SIGAI Career Network and Conference, 2016.
C. Merck, C. Maher, M. Mirtchouk, M. Zheng, Y. Huang and S. Kleinberg. Multimodality Sensing for Eating Recognition. Pervasive Health, 2016.
S. Kleinberg, C. Merck, C. Maher, M. Mirtchouk, M. Zheng, and Y. Huang. Combining Audio and Motion Sensors for Automated Dietary Monitoring. International Conference on Advanced Technologies & Treatments for Diabetes (ATTD), 2016.

Y. Huang and S. Kleinberg. Fast and Accurate Causal Inference from Time Series Data. Florida Artificial Intelligence Research Society Conference (FLAIRS), 2015.
S. Rahman, C. Merck, Y. Huang, and S. Kleinberg. Unintrusive Eating Recognition Using Google Glass. Pervasive Health, 2015 (acceptance rate 16%).
S. Kleinberg, C. Merck, S. Rahman, and Y. Huang. Real-Time Eating Recognition Using Google Glass to Improve Closed-Loop Glucose Control. International Conference on Advanced Technologies & Treatments for Diabetes (ATTD), 2015.

S. Rahman, Y. Huang, J. Claassen, and S. Kleinberg. Imputation of Missing Values in Time Series with Lagged Correlations. IEEE International Conference on Data Mining (ICDM) Workshop on Data Mining in Biomedical Informatics and Healthcare, 2014.

J. Chen, H. Jia, Y. Huang, and D. Liu. Learning the Structure of Dynamic Bayesian Networks with Domain Knowledge. International Conference on Machine Learning and Cybernetics, 2012.

Y. Huang, H. Jia, Y. Zhu, and D. Liu. A Factor Graph Inference Algorithm for Diagnostic Bayesian Networks. International Conference on Natural Computation, 2011.

Y. Huang and Y. Ma. CIGAN: A Python Package for Handling Class Imbalance using Generative Adversarial Networks. arXiv, 2022.

Y. Huang, K. Fields and Y. Ma. A Tutorial on Generative Adversarial Networks with Application to Classification of Imbalanced Data. Statistical Analysis and Data Mining, 2021 (Impact Factor 1.051).
D. He, Y. Wu, Y. Wang, Z. Yu, Z. Feng, X. Wang, and Y. Huang. Identification of Communities with Multi-Semantics via Bayesian Generative Model. IEEE Transactions on Big Data, 2021 (Impact Factor 3.344).
D. He, H. Liu, Z. Feng, X. Wang, D. Jin, W. Song, and Y. Huang. A Joint Community Detection Model: Integrating Directed and Undirected Probabilistic Graphical Models via Factor Graph with Attention Mechanism. IEEE Transactions on Big Data, 2021 (Impact Factor 3.344).
D. He, T. Wang, L. Zhai, D. Jin, L. Yang, Y. Huang, Z. Feng and P. Yu. Adversarial Representation Mechanism Learning for Network Embedding. IEEE Transactions on Knowledge and Data Engineering, 2021 (Impact Factor 6.977)
D. He, Y. Wang, J. Cao, W. Ding, S. Chen, Z. Feng, B. Wang and Y. Huang. A Network Embedding-Enhanced Bayesian Model for Generalized Community Detection in Complex Networks. Information Sciences, 2021 (Impact Factor 5.910).
K. Khysru, D. Jin, Y. Huang, H. Feng, and J. Dang. A Tibetan Language Model that Considers the Relationship Between Suffixes and Functional Words. IEEE Signal Processing Letters, 2021.

J. Claassen, S. Rahman, Y. Huang, H. Frey, J. Schmidt, D. Albers, C. Falo, S. Park, S. Agarwal, E. Connolly, and S. Kleinberg. Causal Structure of Brain Physiology after Brain Injury from Subarachnoid Hemorrhage. PLOS ONE, 11(4), 2016.

S. Rahman, Y. Huang, J. Claassen, N. Heintzman, and S. Kleinberg. Combining Fourier and lagged k-nearest neighbor imputation for biomedical time series data. Journal of Biomedical Informatics (JBI), (58):198-207, 2015.

D. Liu, Y. Huang, Q. Yu, J. Chen, and H. Jia. A Search Problem in Complex Diagnostic Bayesian Networks. Knowledge-Based Systems (KBS), (30):95-103, 2012.
D. He, J. Liu, B. Yang, Y. Huang, D. Liu, and D. Jin. An Ant-Based Algorithm with Local Optimization for Community Detection in Large-Scale Networks. Advances in Complex Systems, 15(8), 2012.

Y. Huang, D. Liu, Y. Zhu, and H. Jia. A Search Algorithm for Inference in Diagnostic Bayesian Networks. Journal of Information and Computational Science, 8(7):1181-1188, 2011.
Y. Zhu, D. Liu, H. Jia, and Y. Huang. Structure Learning of Bayesian Network with Bee Triple-Population Evolution Strategies. International Journal of Advancements in Computing Technology, 3(10), 2011.