Huixin Zhan

According to our database, Huixin Zhan authored at least 28 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Efficient and Scalable Fine-Tune of Language Models for Genome Understanding.

Huixin Zhan, Ying Nian Wu, Zijun Zhang

CoRR, 2024

Defense Against Adversarial Attacks for Neural Representations of Text.

Huixin Zhan, Kun Zhang, Zhong Chen, Victor S. Sheng

Proceedings of the 57th Hawaii International Conference on System Sciences, 2024

2023

Mitigate Gender Bias Using Negative Multi-task Learning.

Liyuan Gao, Huixin Zhan, Victor S. Sheng

Neural Process. Lett., December, 2023

ProPath: Disease-Specific Protein Language Model for Variant Pathogenicity.

Huixin Zhan, Zijun Zhang

CoRR, 2023

Group Lasso with Checkpoints Selection for Biological Data Regression.

Huixin Zhan, Yifan Wang

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2023

Defending the Graph Reconstruction Attacks for Simplicial Neural Networks.

Huixin Zhan, Liyuan Gao, Kun Zhang, Zhong Chen, Victor S. Sheng

Proceedings of the 10th IEEE International Conference on Data Science and Advanced Analytics, 2023

Simplex2vec Backward: From Vectors Back to Simplicial Complex.

Huixin Zhan, Kun Zhang, Zhong Chen, Victor S. Sheng

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Privacy-Preserving Representation Learning for Text-Attributed Networks with Simplicial Complexes.

Huixin Zhan, Victor S. Sheng

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Measuring the Privacy Leakage via Graph Reconstruction Attacks on Simplicial Neural Networks (Student Abstract).

Huixin Zhan, Kun Zhang, Keyi Lu, Victor S. Sheng

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Towards Fair and Selectively Privacy-Preserving Models Using Negative Multi-Task Learning (Student Abstract).

Liyuan Gao, Huixin Zhan, Austin Chen, Victor S. Sheng

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Anomaly Detection in Crowdsourced Work with Interval-Valued Labels.

Makenzie Spurling, Chenyi Hu, Huixin Zhan, Victor S. Sheng

Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2022

Towards Explainable Summary of Crowdsourced Reviews Through Text Mining.

Aaron Moody, Chenyi Hu, Huixin Zhan, Makenzie Spurling, Victor S. Sheng

Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2022

Projection Dual Averaging Based Second-order Online Learning.

Zhong Chen, Huixin Zhan, Victor S. Sheng, Andrea Edwards, Kun Zhang

Proceedings of the IEEE International Conference on Data Mining, 2022

New Threats to Privacy-preserving Text Representations.

Huixin Zhan, Kun Zhang, Chenyi Hu, Victor S. Sheng

Proceedings of the 55th Hawaii International Conference on System Sciences, 2022

Proximal Cost-sensitive Sparse Group Online Learning.

Zhong Chen, Huixin Zhan, Victor S. Sheng, Andrea Edwards, Kun Zhang

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Human-Guided Robot Behavior Learning: A GAN-Assisted Preference-Based Reinforcement Learning Approach.

Huixin Zhan, Feng Tao, Yongcan Cao

IEEE Robotics Autom. Lett., 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

Reinforcement learning-based register renaming policy for simultaneous multithreading CPUs.

Huixin Zhan, Victor S. Sheng, Wei-Ming Lin

Expert Syst. Appl., 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

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Deep Model Compression via Two-Stage Deep Reinforcement Learning.

Huixin Zhan, Wei-Ming Lin, Yongcan Cao

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Gated Graph Neural Networks (GG-NNs) for Abstractive Multi-Comment Summarization.

Huixin Zhan, Kun Zhang, Chenyi Hu, Victor S. Sheng

Proceedings of the 2021 IEEE International Conference on Big Knowledge, 2021

Abstractive Text Summarization via Stacked LSTM^*.

Ireddy Siddhartha, Huixin Zhan, Victor S. Sheng

Proceedings of the International Conference on Computational Science and Computational Intelligence, 2021

Multi-objective Privacy-preserving Text Representation Learning.

Huixin Zhan, Kun Zhang, Chenyi Hu, Victor S. Sheng

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

HGATs: hierarchical graph attention networks for multiple comments integration.

Huixin Zhan, Kun Zhang, Chenyi Hu, Victor S. Sheng

Proceedings of the ASONAM '21: International Conference on Advances in Social Networks Analysis and Mining, Virtual Event, The Netherlands, November 8, 2021

K²-GNN: Multiple Users' Comments Integration with Probabilistic K-Hop Knowledge Graph Neural Networks.

Huixin Zhan, Kun Zhang, Chenyi Hu, Victor S. Sheng

Proceedings of the Asian Conference on Machine Learning, 2021

2019

Deep Model Compression via Deep Reinforcement Learning.

Huixin Zhan, Yongcan Cao

CoRR, 2019

Relationship Explainable Multi-objective Optimization Via Vector Value Function Based Reinforcement Learning.

Huixin Zhan, Yongcan Cao

CoRR, 2019

Relationship Explainable Multi-objective Reinforcement Learning with Semantic Explainability Generation.

Huixin Zhan, Yongcan Cao

CoRR, 2019