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20192024
most citedTowards Overfitting Avoidance: Tuning-free Tensor-aided Multi-user Channel Estimation for 3D Massive MIMO Communications

28 citations · 54 across the 5 of their papers we have counts for

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eess.SP2024

Revisiting Trace Norm Minimization for Tensor Tucker Completion: A Direct Multilinear Rank Learning Approach

Xueke Tong, Hancheng Zhu, Lei Cheng +1

To efficiently express tensor data using the Tucker format, a critical task is to minimize the multilinear rank such that the model would not be over-flexible and lead to overfitti…

eess.SP2023

Overcoming Beam Squint in Dual-Wideband mmWave MIMO Channel Estimation: A Bayesian Multi-Band Sparsity Approach

Le Xu, Lei Cheng, Ngai Wong +2

The beam squint effect, which manifests in different steering matrices in different sub-bands, has been widely considered a challenge in millimeter wave (mmWave) multiinput multi-o…

eess.SP2023

To Fold or Not to Fold: Graph Regularized Tensor Train for Visual Data Completion

Le Xu, Lei Cheng, Ngai Wong +1

Tensor train (TT) representation has achieved tremendous success in visual data completion tasks, especially when it is combined with tensor folding. However, folding an image or v…

eess.SP202128 cited

Towards Overfitting Avoidance: Tuning-free Tensor-aided Multi-user Channel Estimation for 3D Massive MIMO Communications

Lei Cheng, Qingjiang Shi

Channel estimation has long been deemed as one of the most critical problems in three-dimensional (3D) massive multiple-input multiple-output (MIMO), which is recognized as the lea…

eess.SP20201 cited

Edge Learning with Unmanned Ground Vehicle: Joint Path, Energy and Sample Size Planning

Dan Liu, Shuai Wang, Zhigang Wen +3

Edge learning (EL), which uses edge computing as a platform to execute machine learning algorithms, is able to fully exploit the massive sensing data generated by Internet of Thing…