Differentiable Architecture Search Based on Coordinate Descent
IEEE Access, 2021 Neural architecture search (NAS) is an automated method searching for the optimal network architecture by optimizing the combinations of edges and operations.
Pyunghwan Ahn +2 more
doaj +4 more sources
Differentiable Neural Architecture, Mixed Precision and Accelerator Co-Search [PDF]
IEEE Access, 2023 Quantization, effective Neural Network architecture, and efficient accelerator hardware are three important design paradigms to maximize accuracy and efficiency.
Krishna Teja Chitty-Venkata +4 more
doaj +3 more sources
Image classification optimization technology based on differentiable neural architecture search improvement model [PDF]
PLoS ONEImage classification, as the core task of computer vision, has broad application value in fields such as medical diagnosis and intelligent transportation.However, the ability of differentiable neural architecture to search (NAS) for local information is ...
Yuxuan Ji, Wenshu Li, Nan Yu
doaj +3 more sources
Inner Loop-Based Modified Differentiable Architecture Search
IEEE AccessDifferentiable 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 +3 more sources
EEG-Based Emotion Estimation Model Integrating Structural and Time-Series Information Based on Deep Learning Architecture Optimization [PDF]
SensorsEmotion recognition is increasingly important for applications in mental health and personalized marketing. Traditional methods based on facial and vocal cues lack robustness due to voluntary control, motivating the use of EEG signals that capture neural
Kota Tsuji, Keiko Ono, Takuya Futagami
doaj +2 more sources
Differentiable Neural Architecture Search Method for Blind Image Deblurring [PDF]
Jisuanji gongcheng, 2021 The design of neural networks for image deblurring requires heavy work of manual parameter tuning. To address the problem, a differentiable neural network search method for image deblurring is proposed.
MIAO Si, ZHU Yongxin
doaj +1 more source
Group Differentiable Architecture Search
IEEE Access, 2021 Differentiable architecture search (DARTS) has received great attention due to its simplicity and efficiency. However, there are two annoying problems. One is that searched architecture of normal cell tends to be shallow.
Chaoyuan Shen, Jinhua Xu
doaj +1 more source
IEEE Access, 2022 We present a Model Uncertainty-aware Differentiable ARchiTecture Search ( $\mu $ DARTS) that optimizes neural networks to simultaneously achieve high accuracy and low uncertainty. We introduce concrete dropout within DARTS cells and include a Monte-Carlo
Biswadeep Chakraborty +1 more
doaj +1 more source
A Fast and Progressive Convolutional Neural Architecture Search Algorithm [PDF]
Jisuanji gongcheng, 2022 Manually designing a Convolutional Neural Network(CNN) architecture is extremely difficult and requires a high level of professionalism.The gradient differentiable search is fast and efficient.However, this method has some drawbacks, such as a large gap ...
ZHAO Liang, FANG Wei
doaj +1 more source
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