Long Shi

I am an assistant professor at the School of Computing and Artificial Intelligence at Southwestern University of Finance and Economics. My research interests lie at the intersection of signal processing and machine learning.

I received my Doctoral degree from the School of Electricity Engineering at Southwest Jiaotong University. From 2018 to 2019, I was a visiting student at the University of York under the supervision of Prof. Yuriy Zakharov. I have published several high-quality papers in IEEE TSP, IEEE SPL, IEEE TCSII, SP, DSP, etc. My homepage on Southwestern University of Finance and Economics can be found in myswufe.

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My research focuses on the intersection of signal processing and machine learning. Specifically, I am interested in adaptive signal processing, including algorithm optimization and applications. Additionally, I am interested in machine learning techniques such as subspace clustering, multi-view learning, multimodal learning, and reinforcement learning. Currently, I am also focusing on LLM.

We propose an enhanced multi-view subspace clustering method by constructing an augmented data matrix.

We propose an enhanced multi-view subspace clustering method by constructing an augmented data matrix.

We propose a robust kernel adaptive filtering algorithm by limiting the energy of the weight update within a dynamic threshold.

We propose a novel robust subspace clustering method for image segmentation.

An efficient parameter optimization scheme simutaneously involving step-size and kernel width is proposed for MCC.

We propose a robust kernel method for nonlinear time series prediction.

We propose a novel step-size scheme for complex-valued APA.

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