Zhidi Lin

According to our database, Zhidi Lin authored at least 18 papers between 2018 and 2024.

Collaborative distances:

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

2024

Ensemble Kalman Filtering Meets Gaussian Process SSM for Non-Mean-Field and Online Inference.

Zhidi Lin, Yiyong Sun, Feng Yin, Alexandre Hoang Thiery

IEEE Trans. Signal Process., 2024

Hybrid Data-Driven SSM for Interpretable and Label-Free mmWave Channel Prediction.

Yiyong Sun, Jiajun He, Zhidi Lin, Wenqiang Pu, Feng Yin, Hing Cheung So

CoRR, 2024

Scalable Random Feature Latent Variable Models.

Ying Li, Zhidi Lin, Yuhao Liu, Michael Minyi Zhang, Pablo M. Olmos, Petar M. Djuric

CoRR, 2024

Preventing Model Collapse in Gaussian Process Latent Variable Models.

Ying Li, Zhidi Lin, Feng Yin, Michael Minyi Zhang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Towards Efficient Modeling and Inference in Multi-Dimensional Gaussian Process State-Space Models.

Zhidi Lin, Juan Maroñas, Ying Li, Feng Yin, Sergios Theodoridis

Proceedings of the IEEE International Conference on Acoustics, 2024

Regularization-Based Efficient Continual Learning in Deep State-Space Models.

Yuanhang Zhang, Zhidi Lin, Yiyong Sun, Feng Yin, Carsten Fritsche

Proceedings of the 27th International Conference on Information Fusion, 2024

2023

Gaussian Processes with Linear Multiple Kernel: Spectrum Design and Distributed Learning for Multi-Dimensional Data.

Richard Cornelius Suwandi, Zhidi Lin, Feng Yin

CoRR, 2023

Towards Flexibility and Interpretability of Gaussian Process State-Space Model.

Zhidi Lin, Feng Yin

CoRR, 2023

Output-Dependent Gaussian Process State-Space Model.

Zhidi Lin, Lei Cheng, Feng Yin, Lexi Xu, Shuguang Cui

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Adaptive Gaussian Process Spectral Kernel Learning for 5G Wireless Traffic Prediction.

Xinyi Zhang, Chenxu Zhao, Yun Yang, Zhidi Lin, Juntao Wang, Feng Yin

Proceedings of the 32nd IEEE International Workshop on Machine Learning for Signal Processing, 2022

Gaussian Process Regression with Grid Spectral Mixture Kernel: Distributed Learning for Multidimensional Data.

Richard Cornelius Suwandi, Zhidi Lin, Yiyong Sun, Zhiguo Wang, Lei Cheng, Feng Yin

Proceedings of the 25th International Conference on Information Fusion, 2022

2021

Graph Neural Network for Large-Scale Network Localization.

Wenzhong Yan, Di Jin, Zhidi Lin, Feng Yin

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

FedLoc: Federated Learning Framework for Cooperative Localization and Location Data Processing.

Feng Yin, Zhidi Lin, Yue Xu, Qinglei Kong, Deshi Li, Sergios Theodoridis, Shuguang Cui

CoRR, 2020

One-Class Classifier Based Fault Detection in Distribution Systems With Varying Penetration Levels of Distributed Energy Resources.

Zhidi Lin, Dongliang Duan, Qi Yang, Xuemin Hong, Xiang Cheng, Liuqing Yang, Shuguang Cui

IEEE Access, 2020

An Interpretable and Sample Efficient Deep Kernel for Gaussian Process.

Yijue Dai, Tianjian Zhang, Zhidi Lin, Feng Yin, Sergios Theodoridis, Shuguang Cui

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

2019

A Flexible Approach for Human Activity Recognition Based on Broad Learning System.

Zhidi Lin, Haipeng Chen, Qi Yang, Xuemin Hong

Proceedings of the 2019 11th International Conference on Machine Learning and Computing, 2019

2018

Online MEM Based Binary Classification Algorithm for China Mobile Imbalanced Dataset.

Shuqing Lin, Feng Yin, Zhidi Lin, Yanbin Lin, Shuguang Robert Cui, Teng Li, Fengli Yu, Wei Yu, Xuemin Hong, Jianghong Shi, Zhi-Quan Tom Luo

Proceedings of the IEEE/CIC International Conference on Communications in China, 2018

One-Class Classifier Based Fault Detection in Distribution Systems with Distributed Energy Resources.

Zhidi Lin, Dongliang Duan, Qi Yang, Xiang Cheng, Liuqing Yang, Shuguang Cui

Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018