77 citations · 179 across the 6 of their papers we have counts for
6 papers
Uncovering Bias in Foundation Models: Impact, Testing, Harm, and Mitigation
Shuzhou Sun, Li Liu, Yongxiang Liu +4
Bias in Foundation Models (FMs) - trained on vast datasets spanning societal and historical knowledge - poses significant challenges for fairness and equity across fields such as h…
Blind Super-Resolution via Meta-learning and Markov Chain Monte Carlo Simulation
Jingyuan Xia, Zhixiong Yang, Shengxi Li +4
Learning-based approaches have witnessed great successes in blind single image super-resolution (SISR) tasks, however, handcrafted kernel priors and learning based kernel priors ar…
A Dynamic Kernel Prior Model for Unsupervised Blind Image Super-Resolution
Zhixiong Yang, Jingyuan Xia, Shengxi Li +5
Deep learning-based methods have achieved significant successes on solving the blind super-resolution (BSR) problem. However, most of them request supervised pre-training on labell…
Joint Beamforming Optimization for Active STAR-RIS-Assisted ISAC Systems
Shuang Zhang, Wanming Hao, Gangcan Sun +4
In this paper, we investigate an active simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted integrated sensing and communications (ISA…
Boosting Convolutional Neural Networks with Middle Spectrum Grouped Convolution
Zhuo Su, Jiehua Zhang, Tianpeng Liu +4
This paper proposes a novel module called middle spectrum grouped convolution (MSGC) for efficient deep convolutional neural networks (DCNNs) with the mechanism of grouped convolut…
A Learning Aided Flexible Gradient Descent Approach to MISO Beamforming
Zhixiong Yang, Jing-Yuan Xia, Junshan Luo +2
This paper proposes a learning aided gradient descent (LAGD) algorithm to solve the weighted sum rate (WSR) maximization problem for multiple-input single-output (MISO) beamforming…