AutoML.org

Freiburg-Hannover-Tübingen

Literature on Neural Architecture Search

Maintained by Difan Deng and Marius Lindauer.

The following list considers papers related to neural architecture search. It is by no means complete. If you miss a paper on the list, please let us know.

Please note that although NAS methods steadily improve, the quality of empirical evaluations in this field are still lagging behind compared to other areas in machine learning, AI and optimization. We would therefore like to share some best practices for empirical evaluations of NAS methods, which we believe will facilitate sustained and measurable progress in the field. If you are interested in a teaser, please read our blog post or directly jump to our checklist.

Transformers have gained increasing popularity in different domains. For a comprehensive list of papers focusing on Neural Architecture Search for Transformer-Based spaces, the awesome-transformer-search repo is all you need.

4181 entries « ‹ 22 of 84 › »

2024

3131.

SUZUKI, Shota; ONO, Satoshi

Self-supervised Neural Architecture Search for Multimodal Deep Neural Networks Journal Article

In: IEICE Transactions on Information and Systems, vol. advpub, pp. 2024EDL8018, 2024.

3130.

Ramírez-Gordillo, Tamai; Mora, Higinio; Pujol, Francisco A.; Maciá-Lillo, Antonio

Federated Neural Architecture Search for Efficient and Privacy-Preserving Model Training Proceedings Article

In: 2024 IEEE International Conference on Smart Internet of Things (SmartIoT), pp. 129-136, 2024.

3129.

Nieber, Christian; Dias, Douglas Mota; Garcia, Enrique Naredo; Ryan, Conor

Step Size Control in Evolutionary Algorithms for Neural Architecture Search Proceedings Article

In: Marcelloni, Francesco; Madani, Kurosh; Stein, Niki; Joaquim, Joaquim (Ed.): Proceedings of the 16th International Joint Conference on Computational Intelligence, IJCCI 2024, pp. 288–295, Science and Technology Publications, Lda, 2024, ISBN: 9789897587214, (Publisher Copyright: © 2024 by SCITEPRESS – Science and Technology Publications, Lda.; 16th International Joint Conference on Computational Intelligence, IJCCI 2024 ; Conference date: 20-11-2024 Through 22-11-2024).

Abstract | Links | BibTeX

@inproceedings{8de6b06884fb47c39c21435afd300c51,

title = {Step Size Control in Evolutionary Algorithms for Neural Architecture Search},

author = {Christian Nieber and Douglas Mota Dias and Enrique Naredo Garcia and Conor Ryan},

editor = {Francesco Marcelloni and Kurosh Madani and Niki Stein and Joaquim Joaquim},

url = {https://pure-test.ul.ie/en/publications/step-size-control-in-evolutionary-algorithms-for-neural-architect},

doi = {10.5220/0013013800003837},

isbn = {9789897587214},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

booktitle = {Proceedings of the 16th International Joint Conference on Computational Intelligence, IJCCI 2024},

pages = {288–295},

publisher = {Science and Technology Publications, Lda},

series = {International Joint Conference on Computational Intelligence},

abstract = {This work examines how evolutionary Neural Architecture Search (NAS) algorithms can be improved by controlling the step size of the mutation of numerical parameters. The proposed NAS algorithms are based on F-DENSER, a variation of Dynamic Structured Grammatical Evolution (DSGE). Overall, a (1+5) Evolutionary Strategy is used. Two methods of controlling the step size of mutations of numeric values are compared to Random Search and F-DENSER: Decay of the step size over time and adaptive step size for mutations. The search for lightweight, LeNet-like CNN architectures for MNIST classification is used as a benchmark, optimizing for both accuracy and small architectures. An architecture is described by about 30 evolvable parameters. Experiments show that with step size control, convergence is faster, better performing neural architectures are found on average, and with lower variance. The smallest architecture found during the experiments reached an accuracy of 98.8% on MNIST with only 5,450 free parameters, compared to the 62,158 parameters of LeNet-5.},

note = {Publisher Copyright: © 2024 by SCITEPRESS – Science and Technology Publications, Lda.; 16th International Joint Conference on Computational Intelligence, IJCCI 2024 ; Conference date: 20-11-2024 Through 22-11-2024},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

3128.

Mo, Shibing; Wu, Kai; Gao, Qixuan; Teng, Xiangyi; Liu, Jing

AutoSGNN: Automatic Propagation Mechanism Discovery for Spectral Graph Neural Networks Technical Report

2024.

3127.

Lee, Matthew; Bragman, Felix John Samuel; Sanchez-Matilla, Ricardo; Luengo, Imanol; Stoyanov, Danail

Spatial-Temporal NAS for Fast Surgical Segmentation Proceedings Article

In: 35th British Machine Vision Conference 2024, BMVC 2024, Glasgow, UK, November 25-28, 2024, BMVA, 2024.

3126.

Fang, Yujing; Lu, Hang; Xiao, Dongming; Li, Jiebo

Attention-boosted path exploration neural architecture search for fault diagnosis of rotating machinery Journal Article

In: IEEE Sensors Journal, pp. 1-1, 2024.

3125.

Muscalagiu, Anca-Ioana

Quantum Neural Network Design via Quantum Deep Reinforcement Learning Conference

Proceedings of the 16th International Joint Conference on Computational Intelligence - Volume 1: NCTA, INSTICC SciTePress, 2024, ISBN: 978-989-758-721-4.

3124.

Yang, Yuqian; Zhao, Cong

KNAS-TP: Domain Knowledge-driven Automated Construction of Uplink and Downlink Throughput Predictor in 5G Proceedings Article

In: 2024 16th International Conference on Communication Software and Networks (ICCSN), pp. 173-178, 2024.

3123.

Oh, Youngmin; Lee, Hyunju; Ham, Bumsub

Efficient Few-Shot Neural Architecture Search by Counting the Number of Nonlinear Functions Technical Report

2024.

3122.

Yaoming, Wang; Yuchen, Liu; Wenrui, Dai; Chenglin, Li; Xiaopeng, Zhang; Junni, Zou; Hongkai, Xiong

Variational Dropout for Differentiable Neural Architecture Search Journal Article

In: Chinese Journal of Electronics, vol. 34, pp. 1-18, 2024.

3121.

Sarmiento-Rosales, Sergio; Escalona-Llaguno, Martha

Comparative study on predicting dose equivalent rate using advanced machine learning techniques and time series models Proceedings Article

In: 2024.

3120.

Zhang, Renjie; Lin, Di; Wang, Xin; Baciu, George; Chen, C. L. Philip; Li, Ping

Accurate-PGNet: Learning to Assemble Perceptual Body Parts for Accurate Human Skeleton Establishment Journal Article

In: IEEE Transactions on Multimedia, pp. 1-16, 2024.

3119.

Mao, Shouren; Qin, Minghao; Dong, Wei; Liu, Huajian; Gao, Yongzhuo

RAM-NAS: Resource-aware Multiobjective Neural Architecture Search Method for Robot Vision Tasks Proceedings Article

In: 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 2712-2719, 2024.

3118.

RV, Rashmitha

Automated ASIC Design Optimization Using Neural Architecture Search Techniques Journal Article

In: International Journal of Current Research in Science, Engineering & Technology, vol. 7, pp. 95-102, 2024.

3117.

Tao, Devon; Bang, Lucas

Fitness Landscape Analysis of a Cell-Based Neural Architecture Search Space Conference

Proceedings of the 1st International Conference on Explainable AI for Neural and Symbolic Methods - Volume 1: EXPLAINS, INSTICC SciTePress, 2024, ISBN: 978-989-758-720-7.

3116.

Guo, Daidou; Qin, Chuan

PCMark-NAS: Lightweight Print-Camera Resilient Watermarking Networks via Neural Architecture Search Proceedings Article

In: Proceedings of the 6th ACM International Conference on Multimedia in Asia, Association for Computing Machinery, New York, NY, USA, 2024, ISBN: 9798400712739.

Abstract | Links | BibTeX

3115.

Silva, Diego A.; Elsheikh, Ahmed; Smagulova, Kamilya; Fouda, Mohammed E.; Eltawil, Ahmed M.

Chimera: A Block-Based Neural Architecture Search Framework for Event-Based Object Detection Technical Report

2024.

3114.

Ravindran, Saranya; Rajagopalan, Sasikumar

PNasFH-Net: Pyramid Neural Architecture Search Forward Network for Facial Emotion Recognition in Uncontrolled and Pose Variant Environment Journal Article

In: Knowledge-Based Systems, pp. 112944, 2024, ISSN: 0950-7051.

Abstract | Links | BibTeX

@article{RAVINDRAN2024112944,

title = {PNasFH-Net: Pyramid Neural Architecture Search Forward Network for Facial Emotion Recognition in Uncontrolled and Pose Variant Environment},

author = {Saranya Ravindran and Sasikumar Rajagopalan},

url = {https://www.sciencedirect.com/science/article/pii/S0950705124015788},

doi = {https://doi.org/10.1016/j.knosys.2024.112944},

issn = {0950-7051},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

journal = {Knowledge-Based Systems},

pages = {112944},

abstract = {Face emotion recognition has attracted more attention in recent years because of its wide range of applications. This framework represents a novel facial emotion recognition technique known as a Pyramid Neural Architecture Search Forward Network (PNasFH-Net) developed for face emotion recognition. At first, the input image is subjected to image denoising and contrast enhancement using the Type II Fuzzy System and Cuckoo Search Optimization Algorithm (T2FCS) filter. Then, face detection is performed using the Viola-Jones algorithm based on the resultant denoised contrast-enhanced image. Subsequently, different features, like Spider Local Image Features (SLIF) with entropy, and Local Directional Number Pattern (LDNP) are extracted from the detected face in the feature extraction phase. Finally, facial emotions at different poses are recognized from the extracted features using PNasFH-Net. Here, PNasFH-Net is developed by the integration of the Deep Pyramidal Residual Network (PyramidNet) and NASNet. The recognized classes are surprise, sad, neutral, happy, fear, disgust, contempt and anger. The benchmark dataset for facial expression recognition, AffectNet is employed to assess the performance of the proposed model using performance measures, such as accuracy, TPR, and TNR. In addition, the developed PNasFH-Net obtained a higher accuracy of 90.315%, True Negative Rate (TNR) of 90.157% and True Positive Rate (TPR) of 91.047%.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

3113.

Yan, Xueming; Huang, Han; Jin, Yaochu; Wang, Zilong; Hao, Zhifeng

Neural Architecture Search Based on Bipartite Graphs for Text Classification Journal Article

In: IEEE Transactions on Neural Networks and Learning Systems, pp. 1-15, 2024.

3112.

Sarmiento-Rosales, Sergio; García, Jesús Llano; Falcón-Cardona, Jesús; Monroy, Raúl; Llano, Manuel Casillas; Sosa-Hernández, Víctor

Surrogate Modeling for Efficient Evolutionary Multi-Objective Neural Architecture Search in Super Resolution Image Restoration Conference

Proceedings of the 16th International Joint Conference on Computational Intelligence - Volume 1: ECTA, INSTICC SciTePress, 2024, ISBN: 978-989-758-721-4.

3111.

Yang, Zekang; Zeng, Wang; Jin, Sheng; Qian, Chen; Luo, Ping; Liu, Wentao

NADER: Neural Architecture Design via Multi-Agent Collaboration Technical Report

2024.

3110.

Nguyen, Nam Hoang

Design and Optimization of Deep Neural Networks for Multi-Label Classification on Smart Electrical Devices Monitoring System Proceedings Article

In: 2024 13th International Conference on Control, Automation and Information Sciences (ICCAIS), pp. 1-5, 2024.

3109.

Rajesh, Chilukamari; Sadam, Ravichandra; Kumar, Sushil

Automated Deep Learning Models for Medical Image Segmentation and Denoising Proceedings Article

In: 2024 17th International Conference on Signal Processing and Communication System (ICSPCS), pp. 1-7, 2024.

3108.

Bansal, Divyansh; Al-Jawahry, Hassan M.; Al-Farouni, Mohammed; Kumar, Raman; Kaur, Kamaljeet; Bhosle, Nilesh

Neural Architecture Search (NAS) for Vision Tasks Proceedings Article

In: 2024 4th International Conference on Technological Advancements in Computational Sciences (ICTACS), pp. 1964-1969, 2024.

3107.

Paolini, Emilio; Andriolli, Nicola; Cococcioni, Marco

Enhancing Neuromorphic Photonic Hardware Performance through Neural Architecture Search Proceedings Article

In: 2024.

3106.

Wang, Zhenrong; Li, Weifeng; Xie, Jinghao; Li, Bin

An Automatic Design Method for Dynamic Detection Networks of Industrial Surface Defects Proceedings Article

In: 2024 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), pp. 1449-1453, 2024.

3105.

(Ed.)

Multi-objective evolutionary algorithm based graph neural network architecture search Collection

2024.

3104.

(Ed.)

NAS-FL:Fingerprint Localization Method Based on Automatically Designed Neural Network Architecture Collection

2024.

3103.

Lan, Zheng; Wang, Bo; Liu, Senting; Shi, Xiupeng

CoDANet: Hardware-Aware Neural Architecture Search for Optimized Deep Learning on FPGAs Proceedings Article

In: 2024 2nd International Conference on Artificial Intelligence and Automation Control (AIAC), pp. 563-568, 2024.

3102.

Ayebo, Iyanu; Olatunde, Emma

Neural Architecture Search: Automating Deep Learning Model Design Journal Article

In: 2024.

3101.

Krstic, Lazar; Ivanovic, Milos; Simic, Visnja; Stojanovic, Boban

Evolutionary approach for composing a thoroughly optimized ensemble of regression neural networks Journal Article

In: Egyptian Informatics Journal, vol. 28, pp. 100581, 2024, ISSN: 1110-8665.

Abstract | Links | BibTeX

2023

3100.

(Ed.)

Designing a New Search Space for Multivariate Time-Series Neural Architecture Search Collection

2023.

3099.

Zhao, Junbo; Ning, Xuefei; Liu, Enshu; Ru, Binxin; Zhou, Zixuan; Zhao, Tianchen; Chen, Chen; Zhang, Jiajin; Liao, Qingmin; Wang, Yu

Dynamic Ensemble of Low-fidelity Experts: Mitigating NAS “Cold-Start” Technical Report

2023.

3098.

Zhang, Baochang; Xu, Sheng; Lin, Mingbao; Wang, Tiancheng; Doermann, David

Binary Neural Networks: Algorithms, Architectures, and Applications Book

2023.

3097.

(Ed.)

Multi-task Graph Neural Architecture Search with Task-aware Collaboration and Curriculum Collection

2023.

3096.

(Ed.)

Unsupervised Graph Neural Architecture Search with Disentangled Self-supervision Collection

2023.

3095.

(Ed.)

MathNAS: If Blocks Have a Role in Mathematical Architecture Design Collection

2023.

3094.

(Ed.)

KD-Zero: Evolving Knowledge Distiller for Any Teacher-Student Pairs Collection

2023.

3093.

(Ed.)

Analyzing Generalization of Neural Networks through Loss Path Kernels Collection

2023.

3092.

(Ed.)

Operation-Level Early Stopping for Robustifying Differentiable NAS Collection

2023.

3091.

(Ed.)

AutoGO: Automated Computation Graph Optimization for Neural Network Evolution Collection

2023.

3090.

(Ed.)

Building A Mobile Text Recognizer via Truncated SVD-based Knowledge Distillation-Guided NAS Collection

2023.

3089.

Wang, Shang; Tang, Huangrong

GRADIENT-FREE PROXY FOR EFFICIENT LANGUAGE MODEL SEARCH Technical Report

2023.

3088.

Hundhausen, Felix; Hubschneider, Simon; Asfou, Tamim

Grasping with Humanoid Hands based on In-Hand Vision and Hardware-accelerated CNNs Technical Report

2023.

3087.

Xue, Yu; Tong, Weinan; Neri, Ferrante; Chen, Peng; Luo, Tao; Zhen, Liangli; Wang, Xiao

Evolutionary Architecture Search for Generative Adversarial Networks Based On Weight Sharing Technical Report

2023.

3086.

Al-Sabri, Raeed; Gao, Jianliang; Chen, Jiamin; Oloulade, Babatounde Moctard; Lyu, Tengfei

AutoTGRL: an automatic text-graph representation learning framework Journal Article

In: Neural Computing and Applications, 2023.

3085.

SASNAUSKAS, PAULIUS; PETKEVIČIUS, INAS

Symbolic Neural Architecture Search for Differential Equations Journal Article

In: 2023.

3084.

Luo, Xiangzhong

Hardware-aware neural architecture search and compression towards embedded intelligence PhD Thesis

2023.

3083.

Huai, Shuo

Enabling efficient edge intelligence: a hardware-software codesign approach PhD Thesis

2023.

3082.

(Ed.)

Improving Natural Language Understanding with Computation-Efficient Retrieval Representation Fusion Collection

2023.

4181 entries « ‹ 22 of 84 › »