Zobrazeno 1 - 10
of 4 731
pro vyhledávání: '"WANG Feifei"'
We investigate LoRA in federated learning through the lens of the asymmetry analysis of the learned $A$ and $B$ matrices. In doing so, we uncover that $A$ matrices are responsible for learning general knowledge, while $B$ matrices focus on capturing
Externí odkaz:
http://arxiv.org/abs/2410.01463
Deep learning, particularly convolutional neural networks (CNNs) and Transformers, has significantly advanced 3D medical image segmentation. While CNNs are highly effective at capturing local features, their limited receptive fields may hinder perfor
Externí odkaz:
http://arxiv.org/abs/2409.12533
Autor:
Li, Xuetong, Gao, Yuan, Chang, Hong, Huang, Danyang, Ma, Yingying, Pan, Rui, Qi, Haobo, Wang, Feifei, Wu, Shuyuan, Xu, Ke, Zhou, Jing, Zhu, Xuening, Zhu, Yingqiu, Wang, Hansheng
This paper presents a selective review of statistical computation methods for massive data analysis. A huge amount of statistical methods for massive data computation have been rapidly developed in the past decades. In this work, we focus on three ca
Externí odkaz:
http://arxiv.org/abs/2403.11163
Autor:
Wang, Feifei
This technical report presents a diffusion model based framework for face swapping between two portrait images. The basic framework consists of three components, i.e., IP-Adapter, ControlNet, and Stable Diffusion's inpainting pipeline, for face featu
Externí odkaz:
http://arxiv.org/abs/2403.01108
Despite the success of diffusion-based customization methods on visual content creation, increasing concerns have been raised about such techniques from both privacy and political perspectives. To tackle this issue, several anti-customization methods
Externí odkaz:
http://arxiv.org/abs/2312.07865
Federated learning is an emerging distributed machine learning framework aiming at protecting data privacy. Data heterogeneity is one of the core challenges in federated learning, which could severely degrade the convergence rate and prediction perfo
Externí odkaz:
http://arxiv.org/abs/2312.04281
Autor:
Sun, Hui, Luo, Hao, Wang, Feifei, Chen, Qingjiu, Chen, Meng, Wang, Xiaoduo, Yu, Haibo, Zhang, Guanglie, Liu, Lianqing, Wang, Jianping, Wu, Dapeng, Li, Wen Jung
Scanning electron microscopy (SEM) is indispensable in diverse applications ranging from microelectronics to food processing because it provides large depth-of-field images with a resolution beyond the optical diffraction limit. However, the technolo
Externí odkaz:
http://arxiv.org/abs/2310.17997
Investments in research and development are key to scientific and economic growth and to the well-being of society. Scientific research demands significant resources making national scientific investment a crucial driver of scientific production. As
Externí odkaz:
http://arxiv.org/abs/2308.08630
Autor:
Liang, Peng, Zhu, Guanzhou, Huang, Cheng-Liang, Li, Yuan-Yao, Sun, Hao, Yuan, Bin, Wu, Shu-Chi, Li, Jiachen, Wang, Feifei, Hwang, Bing-Joe, Dai, Hongjie
Low temperature rechargeable batteries are important to life in cold climates, polar/deep-sea expeditions and space explorations. Here, we report ~ 3.5 - 4 V rechargeable lithium/chlorine (Li/Cl2) batteries operating down to -80 {\deg}C, employing Li
Externí odkaz:
http://arxiv.org/abs/2307.12947
Large-scale networks are commonly encountered in practice (e.g., Facebook and Twitter) by researchers. In order to study the network interaction between different nodes of large-scale networks, the spatial autoregressive (SAR) model has been popularl
Externí odkaz:
http://arxiv.org/abs/2306.04093