activity
20162024
most citedRepPoints V2: Verification Meets Regression for Object Detection

70 citations · 302 across the 27 of their papers we have counts for

collaborators

41 papers

cs.CV2024

CDIMC-net: Cognitive Deep Incomplete Multi-view Clustering Network

Jie Wen, Zheng Zhang, Yong Xu +3

In recent years, incomplete multi-view clustering, which studies the challenging multi-view clustering problem on missing views, has received growing research interests. Although a…

cs.LG20236 cited

Tensor-Compressed Back-Propagation-Free Training for (Physics-Informed) Neural Networks

Yequan Zhao, Xinling Yu, Zhixiong Chen +3

Backward propagation (BP) is widely used to compute the gradients in neural network training. However, it is hard to implement BP on edge devices due to the lack of hardware and so…

cs.RO2023

Reinforced Potential Field for Multi-Robot Motion Planning in Cluttered Environments

Dengyu Zhang, Xinyu Zhang, Zheng Zhang +2

Motion planning is challenging for multiple robots in cluttered environments without communication, especially in view of real-time efficiency, motion safety, distributed computati…

cs.CV2023

KECOR: Kernel Coding Rate Maximization for Active 3D Object Detection

Yadan Luo, Zhuoxiao Chen, Zhen Fang +3

Achieving a reliable LiDAR-based object detector in autonomous driving is paramount, but its success hinges on obtaining large amounts of precise 3D annotations. Active learning (A…

cs.CL2023

Quantization-Aware and Tensor-Compressed Training of Transformers for Natural Language Understanding

Zi Yang, Samridhi Choudhary, Siegfried Kunzmann +1

Fine-tuned transformer models have shown superior performances in many natural language tasks. However, the large model size prohibits deploying high-performance transformer models…

math.ST2022

Nonparametric Estimation of the Continuous Treatment Effect with Measurement Error

Wei Huang, Zheng Zhang

We identify the average dose-response function (ADRF) for a continuously valued error-contaminated treatment by a weighted conditional expectation. We then estimate the weights non…