29 citations · 34 across the 8 of their papers we have counts for
8 papers
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…
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…
Weight-Inherited Distillation for Task-Agnostic BERT Compression
Taiqiang Wu, Cheng Hou, Shanshan Lao +4
Knowledge Distillation (KD) is a predominant approach for BERT compression. Previous KD-based methods focus on designing extra alignment losses for the student model to mimic the b…
Context-Aware Transformer for 3D Point Cloud Automatic Annotation
Xiaoyan Qian, Chang Liu, Xiaojuan Qi +3
3D automatic annotation has received increased attention since manually annotating 3D point clouds is laborious. However, existing methods are usually complicated, e.g., pipelined…
Edge-free but Structure-aware: Prototype-Guided Knowledge Distillation from GNNs to MLPs
Taiqiang Wu, Zhe Zhao, Jiahao Wang +4
Distilling high-accuracy Graph Neural Networks (GNNs) to low-latency multilayer perceptions (MLPs) on graph tasks has become a hot research topic. However, conventional MLP learnin…
Frequency Regularization for Improving Adversarial Robustness
Binxiao Huang, Chaofan Tao, Rui Lin +1
Deep neural networks are incredibly vulnerable to crafted, human-imperceptible adversarial perturbations. Although adversarial training (AT) has proven to be an effective defense a…
Multimodal Transformer for Automatic 3D Annotation and Object Detection
Chang Liu, Xiaoyan Qian, Binxiao Huang +4
Despite a growing number of datasets being collected for training 3D object detection models, significant human effort is still required to annotate 3D boxes on LiDAR scans. To aut…
Tensor Train Factorization and Completion under Noisy Data with Prior Analysis and Rank Estimation
Le Xu, Lei Cheng, Ngai Wong +1
Tensor train (TT) decomposition, a powerful tool for analyzing multidimensional data, exhibits superior performance in many machine learning tasks. However, existing methods for TT…