Relationship Explainable Multi-objective Reinforcement Learning with Semantic Explainability Generation. - Huixin Zhan; Yongcan Cao (CoRR, 2019)

Relationship Explainable Multi-objective Optimization Via Vector Value Function Based Reinforcement Learning. - Huixin Zhan; Yongcan Cao (CoRR, 2019)

Deep Model Compression via Deep Reinforcement Learning. - Huixin Zhan; Yongcan Cao (CoRR, 2019)

K2-GNN: Multiple Users' Comments Integration with Probabilistic K-Hop Knowledge Graph Neural Networks. - Huixin Zhan; Kun Zhang 012; Chenyi Hu; Victor S. Sheng (ACML, 2021)

HGATs: hierarchical graph attention networks for multiple comments integration. - Huixin Zhan; Kun Zhang 012; Chenyi Hu; Victor S. Sheng (ASONAM, 2021)

Multi-objective Privacy-preserving Text Representation Learning. - Huixin Zhan; Kun Zhang 012; Chenyi Hu; Victor S. Sheng (CIKM, 2021)

Abstractive Text Summarization via Stacked LSTM*. - Ireddy Siddhartha; Huixin Zhan; Victor S. Sheng (CSCI, 2021)

Gated Graph Neural Networks (GG-NNs) for Abstractive Multi-Comment Summarization. - Huixin Zhan; Kun Zhang 012; Chenyi Hu; Victor S. Sheng (ICBK, 2021)

Deep Model Compression via Two-Stage Deep Reinforcement Learning. - Huixin Zhan; Wei-Ming Lin; Yongcan Cao (ECML/PKDD (1), 2021)

Estimating crowd-worker's reliability with interval-valued labels to improve the quality of crowdsourced work. - Makenzie Spurling; Chenyi Hu; Huixin Zhan; Victor S. Sheng (SSCI, 2021)

Reinforcement learning-based register renaming policy for simultaneous multithreading CPUs. - Huixin Zhan; Victor S. Sheng; Wei-Ming Lin (Expert Syst. Appl., 2021)

Efficient Multi-objective Reinforcement Learning via Multiple-gradient Descent with Iteratively Discovered Weight-Vector Sets. - Yongcan Cao; Huixin Zhan (J. Artif. Intell. Res., 2021)

Human-Guided Robot Behavior Learning: A GAN-Assisted Preference-Based Reinforcement Learning Approach. - Huixin Zhan; Feng Tao 003; Yongcan Cao (IEEE Robotics Autom. Lett., 2021)

Proximal Cost-sensitive Sparse Group Online Learning. - Zhong Chen 003; Huixin Zhan; Victor S. Sheng; Andrea Edwards; Kun Zhang 012 (IEEE Big Data, 2022)

New Threats to Privacy-preserving Text Representations. - Huixin Zhan; Kun Zhang 012; Chenyi Hu; Victor S. Sheng (HICSS, 2022)

Projection Dual Averaging Based Second-order Online Learning. - Zhong Chen 003; Huixin Zhan; Victor S. Sheng; Andrea Edwards; Kun Zhang 012 (ICDM, 2022)

Towards Explainable Summary of Crowdsourced Reviews Through Text Mining. - Aaron Moody; Chenyi Hu; Huixin Zhan; Makenzie Spurling; Victor S. Sheng (IPMU (1), 2022)

Anomaly Detection in Crowdsourced Work with Interval-Valued Labels. - Makenzie Spurling; Chenyi Hu; Huixin Zhan; Victor S. Sheng (IPMU (1), 2022)

Towards Fair and Selectively Privacy-Preserving Models Using Negative Multi-Task Learning (Student Abstract). - Liyuan Gao; Huixin Zhan; Austin Chen; Victor S. Sheng (AAAI, 2023)

Measuring the Privacy Leakage via Graph Reconstruction Attacks on Simplicial Neural Networks (Student Abstract). - Huixin Zhan; Kun Zhang 012; Keyi Lu; Victor S. Sheng (AAAI, 2023)

Privacy-Preserving Representation Learning for Text-Attributed Networks with Simplicial Complexes. - Huixin Zhan; Victor S. Sheng (AAAI, 2023)

Simplex2vec Backward: From Vectors Back to Simplicial Complex. - Huixin Zhan; Kun Zhang 012; Zhong Chen 003; Victor S. Sheng (CIKM, 2023)

Defending the Graph Reconstruction Attacks for Simplicial Neural Networks. - Huixin Zhan; Liyuan Gao; Kun Zhang 012; Zhong Chen 003; Victor S. Sheng (DSAA, 2023)

Group Lasso with Checkpoints Selection for Biological Data Regression. - Huixin Zhan; Yifan Wang (SMC, 2023)

ProPath: Disease-Specific Protein Language Model for Variant Pathogenicity. - Huixin Zhan; Zijun Zhang (CoRR, 2023)

Mitigate Gender Bias Using Negative Multi-task Learning. - Liyuan Gao; Huixin Zhan; Victor S. Sheng (Neural Process. Lett., 2023)

Defense Against Adversarial Attacks for Neural Representations of Text. - Huixin Zhan; Kun Zhang 012; Zhong Chen 003; Victor S. Sheng (HICSS, 2024)

Exploring Task-Specific Dimensions in Word Embeddings Through Automatic Rule Learning. - Liyuan Gao; Huixin Zhan; Victor S. Sheng (ICANN (4), 2024)

Privacy-Preserving Unsupervised Spherical Text Embeddings. - Huixin Zhan; Liyuan Gao; Victor S. Sheng (IJCNN, 2024)

Robust Sparse Online Learning for Data Streams with Streaming Features. - Zhong Chen 003; Yi He 007; Di Wu 056; Huixin Zhan; Victor S. Sheng; Kun Zhang 012 (SDM, 2024)

Efficient and Scalable Fine-Tune of Language Models for Genome Understanding. - Huixin Zhan; Ying Nian Wu; Zijun Zhang (CoRR, 2024)

DYNA: Disease-Specific Language Model for Variant Pathogenicity. - Huixin Zhan; Zijun Zhang (CoRR, 2024)

Long-range gene expression prediction with token alignment of large language model. - Edouardo Honig; Huixin Zhan; Ying Nian Wu; Zijun Frank Zhang (CoRR, 2024)

A disease-specific language model for variant pathogenicity in cardiac and regulatory genomics. - Huixin Zhan; Jason H. Moore; Zijun Zhang (Nat. Mac. Intell., 2025)

SafeGenes: Evaluating the Adversarial Robustness of Genomic Foundation Models. - Huixin Zhan; Jason H. Moore (CoRR, 2025)

Agentic Surgical AI: Surgeon Style Fingerprinting and Privacy Risk Quantification via Discrete Diffusion in a Vision-Language-Action Framework. - Huixin Zhan; Jason H. Moore (CoRR, 2025)