Results 41 to 50 of about 6,207,310 (278)

Differentiable Architecture Search Algorithm Based on Global Comparison

IEEE Access, 2023
Manually building neural network models is a great test of researchers’ knowledge reserves, so using Neural Architecture Search (NAS) to automatically construct neural networks is becoming increasingly popular.
Xianglun Zeng, Hongxiang Xiao
doaj   +1 more source

Graph Convolutional Networks by Architecture Search for PolSAR Image Classification

Remote Sensing, 2021
Classification of polarimetric synthetic aperture radar (PolSAR) images has achieved good results due to the excellent fitting ability of neural networks with a large number of training samples.
Hongying Liu, Derong Xu, Tianwen Zhu, Fanhua Shang, Yuanyuan Liu, Jianhua Lu, Ri Yang   +6 more
doaj   +1 more source

Partial Connection Based on Channel Attention for Differentiable Neural Architecture Search

, 2022
Differentiable neural architecture search (DARTS), as a gradient-guided search method, greatly reduces the cost of computation and speeds up the search. In DARTS, the architecture parameters are introduced to the candidate operations, but the parameters ...
Jiafeng Qin, Xue, Yu, Qin, Jiafeng, Yu Xue   +3 more
core   +1 more source

Inner Loop-Based Modified Differentiable Architecture Search

IEEE Access
Differentiable neural architecture search, which significantly reduces the computational cost of architecture search by several orders of magnitude, has become a popular research issue in recent years.
Cong Jin, Jinjie Huang
doaj   +1 more source

HardCoRe-NAS: Hard Constrained diffeRentiable Neural Architecture Search

CoRR, 2021
Realistic use of neural networks often requires adhering to multiple constraints on latency, energy and memory among others. A popular approach to find fitting networks is through constrained Neural Architecture Search (NAS), however, previous methods enforce the constraint only softly.
Niv Nayman, Yonathan Aflalo, Asaf Noy, Lihi Zelnik   +3 more
openaire   +4 more sources

Operation-level Progressive Differentiable Architecture Search

, 2021
Differentiable Neural Architecture Search (DARTS) is becoming more and more popular among Neural Architecture Search (NAS) methods because of its high search efficiency and low compute cost.
Jian Li, Wang, Weiping, Jun Liao, Zhu, Xunyu, Weiping Wang, Yong Liu, Xunyu Zhu, Liu, Yong, Li, Jian   +8 more
core   +1 more source

U-DARTS: Uniform-space differentiable architecture search [PDF]

, 2023
Differentiable architecture search (DARTS) is an effective neural architecture search algorithm based on gradient descent. However, there are two limitations in DARTS.
Wencong Wang, Huang, Lan, Zeng, Jia, Pang, Wei; id_orcid, Jia Zeng, Sun, Shiqi, Wang, Wencong, Shiqi Sun, Wang, Kangping, Lan Huang, Wei Pang, Kangping Wang   +11 more
core   +1 more source

Overview of Differentiable Neural Network Architecture Search

Zhengzhou Daxue xuebao. Gongxue ban
Neural Architecture Search (NAS) was an interdisciplinary study in the field of deep learning, which aimed to automate the design of neural network structures. NAS required repeated training and evaluation of a large number of candidate networks, which
LU Peng, LI Keyan, ZHANG Hongpo, CHEN Liwei, WU Jiahui, LIU Shuaibing   +5 more
doaj   +1 more source

Remaining Useful Life Estimation of Aircraft Engines Using Differentiable Architecture Search

Mathematics, 2022
Prognostics and health management (PHM) applications can prevent engines from potential serious accidents by predicting the remaining useful life (RUL). Recently, data-driven methods have been widely used to solve RUL problems.
Pengli Mao, Yan Lin, Song Xue, Baochang Zhang   +3 more
doaj   +1 more source

Efficient Differentiable Neural Architecture Search with Meta Kernels

CoRR, 2019
The searching procedure of neural architecture search (NAS) is notoriously time consuming and cost prohibitive.To make the search space continuous, most existing gradient-based NAS methods relax the categorical choice of a particular operation to a softmax over all possible operations and calculate the weighted sum of multiple features, resulting in a ...
Shoufa Chen, Yunpeng Chen, Shuicheng Yan, Jiashi Feng   +3 more
openaire   +3 more sources