Yue Ju

According to our database, Yue Ju authored at least 18 papers between 2020 and 2024.

Collaborative distances:

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

2024

Beamforming Optimization for Hybrid Active-Passive RIS Assisted Wireless Communications: A Rate-Maximization Perspective.

Yue Ju, Shiqi Gong, Heng Liu, Chengwen Xing, Jianping An, Yonghui Li

IEEE Trans. Commun., September, 2024

Robust Federated Finetuning of Foundation Models via Alternating Minimization of LoRA.

Shuangyi Chen, Yue Ju, Hardik Dalal, Zhongwen Zhu, Ashish Khisti

CoRR, 2024

Root Cause Analysis of Anomalies in 5G RAN Using Graph Neural Network and Transformer.

Antor Hasan, Conrado Boeira, Khaleda Papry, Yue Ju, Zhongwen Zhu, Israat Haque

CoRR, 2024

A Calibrated and Automated Simulator for Innovations in 5G.

Conrado Boeira, Antor Hasan, Khaleda Papry, Yue Ju, Zhongwen Zhu, Israat Haque

CoRR, 2024

Calibration and Automation of a 5G Simulator for Realistic Evaluation and Data Generation.

Conrado Boeira, Antor Hasan, Khaleda Papry, Yue Ju, Zhongwen Zhu, Israat Haque

Proceedings of the 10th IEEE International Conference on Network Softwarization, 2024

Secure Inference for Vertically Partitioned Data Using Multiparty Homomorphic Encryption.

Shuangyi Chen, Yue Ju, Zhongwen Zhu, Ashish Khisti

Proceedings of the IEEE International Symposium on Information Theory, 2024

2023

Asymptotic Theory for Regularized System Identification Part I: Empirical Bayes Hyperparameter Estimator.

Yue Ju, Biqiang Mu, Lennart Ljung, Tianshi Chen

IEEE Trans. Autom. Control., December, 2023

Boosting Just-In-Time Code Comment Updating Via Programming Context and Refactor.

Xiangbo Mi, Jingxuan Zhang, Yixuan Tang, Yue Ju, Jinpeng Lan

Int. J. Softw. Eng. Knowl. Eng., October, 2023

An efficient implementation for spatial-temporal Gaussian process regression and its applications.

Junpeng Zhang, Yue Ju, Biqiang Mu, Renxin Zhong, Tianshi Chen

Autom., 2023

A Cross-Language Name Binding Recognition and Discrimination Approach for Identifiers.

Yue Ju, Yixuan Tang, Jinpeng Lan, Xiangbo Mi, Jingxuan Zhang

Proceedings of the IEEE International Conference on Software Analysis, 2023

DeepTD: Diversity-Guided Deep Neural Network Test Generation.

Jin Zhu, Chuanqi Tao, Hongjing Guo, Yue Ju

Proceedings of the Dependable Software Engineering. Theories, Tools, and Applications, 2023

An Efficient Implementation for Bayesian Manifold Regularization Method.

Junpeng Zhang, Yue Ju, Bo Wahlberg, Biqiang Mu, Tianshi Chen

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022

Asymptotic Theory for Regularized System Identification Part I: Empirical Bayes Hyper-parameter Estimator.

Yue Ju, Bi-Qiang Mu, Lennart Ljung, Tianshi Chen

CoRR, 2022

2021

ChunkFormer: Learning Long Time Series with Multi-stage Chunked Transformer.

Yue Ju, Alka Isac, Yimin Nie

CoRR, 2021

Tutorial on Asymptotic Properties of Regularized Least Squares Estimator for Finite Impulse Response Model.

Yue Ju, Tianshi Chen, Bi-Qiang Mu, Lennart Ljung

CoRR, 2021

On Asymptotic Distribution of Generalized Cross Validation Hyper-parameter Estimator for Regularized System Identification^*.

Yue Ju, Tianshi Chen, Bi-Qiang Mu, Lennart Ljung

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2020

On Effects of Condition Number of Regression Matrix upon Hyper-parameter Estimators for Kernel-based Regularization Methods.

Yue Ju, Tianshi Chen, Bi-Qiang Mu, Lennart Ljung

CoRR, 2020

On the Influence of Ill-conditioned Regression Matrix on Hyper-parameter Estimators for Kernel-based Regularization Methods.

Yue Ju, Tianshi Chen, Bi-Qiang Mu, Lennart Ljung

Proceedings of the 59th IEEE Conference on Decision and Control, 2020