Zobrazeno 1 - 10
of 112
pro vyhledávání: '"Zhou, QiHua"'
Recent years have witnessed the vulnerability of Federated Learning (FL) against gradient leakage attacks, where the private training data can be recovered from the exchanged gradients, making gradient protection a critical issue for the FL training
Externí odkaz:
http://arxiv.org/abs/2407.05285
Autor:
Guo, Jingcai, Zhou, Qihua, Li, Ruibing, Lu, Xiaocheng, Liu, Ziming, Chen, Junyang, Xie, Xin, Zhang, Jie
This paper provides a novel parsimonious yet efficient design for zero-shot learning (ZSL), dubbed ParsNets, where we are interested in learning a composition of on-device friendly linear networks, each with orthogonality and low-rankness properties,
Externí odkaz:
http://arxiv.org/abs/2312.09709
Autor:
Rao, Zhijie, Guo, Jingcai, Lu, Xiaocheng, Zhou, Qihua, Zhang, Jie, Wei, Kang, Li, Chenxin, Guo, Song
Generalized Zero-shot Learning (GZSL) has yielded remarkable performance by designing a series of unbiased visual-semantics mappings, wherein, the precision relies heavily on the completeness of extracted visual features from both seen and unseen cla
Externí odkaz:
http://arxiv.org/abs/2311.14750
Autor:
Li, Ruibin, Zhou, Qihua, Guo, Song, Zhang, Jie, Guo, Jingcai, Jiang, Xinyang, Shen, Yifei, Han, Zhenhua
Diffusion-based Generative Models (DGMs) have achieved unparalleled performance in synthesizing high-quality visual content, opening up the opportunity to improve image super-resolution (SR) tasks. Recent solutions for these tasks often train archite
Externí odkaz:
http://arxiv.org/abs/2306.00714
Recent years have witnessed the dramatic growth of Internet video traffic, where the video bitstreams are often compressed and delivered in low quality to fit the streamer's uplink bandwidth. To alleviate the quality degradation, it comes the rise of
Externí odkaz:
http://arxiv.org/abs/2211.08428
To eliminate the requirement of fully-labeled data for supervised model training in traditional Federated Learning (FL), extensive attention has been paid to the application of Self-supervised Learning (SSL) approaches on FL to tackle the label scarc
Externí odkaz:
http://arxiv.org/abs/2211.07364
Autor:
Rao, Richuan, Huang, Yaohua, Zhang, Hao, Hu, Chunming, Dong, Xiongzi, Fang, Weiguang, Zhou, Qihua, Chen, Zhen, Fang, Song, Jin, Dongsheng, Lv, Xinhao, Liu, Baijun, Ling, Qiang
Publikováno v:
In Separation and Purification Technology 11 November 2024 347
Publikováno v:
In Colloids and Surfaces A: Physicochemical and Engineering Aspects 5 October 2024 698
Publikováno v:
In Diamond & Related Materials December 2024 150
Publikováno v:
In Journal of Solid State Chemistry November 2023 327