nepotism
发表于 2025-3-23 12:24:34
Julia Selman Ayetey,Harold Ayeteyunning memory and computing resources hinder the deployment on resource-limited devices. In this paper, we propose an effective method to dynamically enhance the sparsity on channel-level. To this end, we introduce dynamic sparsity coefficient (DSC) to balance model training and sparse training as w
vitrectomy
发表于 2025-3-23 14:18:19
Christoffel Kotzeunning memory and computing resources hinder the deployment on resource-limited devices. In this paper, we propose an effective method to dynamically enhance the sparsity on channel-level. To this end, we introduce dynamic sparsity coefficient (DSC) to balance model training and sparse training as w
Indecisive
发表于 2025-3-23 21:50:13
Nicolas RingasNs may generate redundant information in the message passing phase. In order to solve this problem, we propose a novel graph convolution named Push-and-Pull Convolution (PPC), which follows the message passing framework. On the one hand, for each star-shaped subgraph, PPC uses a node pair based mess
cortex
发表于 2025-3-23 23:08:24
http://reply.papertrans.cn/88/8731/873084/873084_14.png
推迟
发表于 2025-3-24 05:08:25
Khaled Khanbari,Sylvie Leroy,Ahmad Adris,Sami Moheb-Al-Deen,Waheed Al-SarariNs may generate redundant information in the message passing phase. In order to solve this problem, we propose a novel graph convolution named Push-and-Pull Convolution (PPC), which follows the message passing framework. On the one hand, for each star-shaped subgraph, PPC uses a node pair based mess
finite
发表于 2025-3-24 08:27:50
http://reply.papertrans.cn/88/8731/873084/873084_16.png
abreast
发表于 2025-3-24 13:23:38
http://reply.papertrans.cn/88/8731/873084/873084_17.png
LAPSE
发表于 2025-3-24 16:21:44
Annette Froehlichtimation, Edge Estimation, etc. With advanced deep learning, many dense prediction tasks have been greatly improved. Multi-task learning is one of the top research lines to boost task performance further. Properly designed multi-task model architectures have better performance and minor memory usage
减去
发表于 2025-3-24 19:19:33
Temidayo Oniosun,Ndéye Marie Aida Ndieguene,Mwenya Mwamba,Sharon Kendi Amugongo,Oluwafunmilayo Oluwa. Nevertheless, deploying large DNN models on resource-constrained edge devices is still challenging due to limitations in computation, power, and application-specific privacy requirements. Existing model partitioning methods, which deploy a partial DNN on an edge device while processing the remaini
加强防卫
发表于 2025-3-25 00:54:24
Nicolas Ringas,James Wilson,Asim Raza,Bafowethu Setheli,Barbara Amelia King,Jahanzaib Hussain,Luke Cs a feature extractor and replace the classification head with a decoder to generate segmented outputs. The advantage of this strategy is the ability to obtain a ready-made backbone with additional knowledge. However, there are several disadvantages, such as a lack of architectural knowledge, a sign