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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.

4191 entries « ‹ 37 of 84 › »

2023

2391.

Liu, Xuan; Liu, Xiong; Huang, Zhifeng; Zhao, Tianyang

A Compact Neural Network-Based Conversion Loss Model with Hard Constraints for Energy Management Journal Article

In: IEEE Transactions on Industry Applications, pp. 1-13, 2023.

2390.

Aliouat, Wahiba; Badis, Lamis; Bouchiba, Kenza

Metaheuristic-based automated design of Convolutional Neural Network architecture for plant seedlings classification Proceedings Article

In: 2023 5th International Conference on Pattern Analysis and Intelligent Systems (PAIS), pp. 1-8, 2023.

2389.

Dong, Haoyuan; Gao, Yang; Wang, Haishuai; Yang, Hong; Zhang, Peng

Heterogeneous Graph Neural Architecture Search with GPT-4 Technical Report

2023.

2388.

Li, J.; Lv, Y.; Zhang, P.; Zhao, J.

Neural Architecture Search for Unsupervised PET Image Denoising Proceedings Article

In: 2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD), pp. 1-1, 2023.

2387.

Mu, Pan; Wu, Guanyao; Liu, Jinyuan; Zhang, Yuduo; Fan, Xin; Liu, Risheng

Learning to Search a Lightweight Generalized Network for Medical Image Fusion Journal Article

In: IEEE Transactions on Circuits and Systems for Video Technology, pp. 1-1, 2023.

2386.

(Ed.)

Auto-Prox: Training-Free Vision Transformer Architecture Search via Automatic Proxy Discovery Collection

2023.

2385.

Sukthanker, Rhea Sanjay; Krishnakumar, Arjun; Safari, Mahmoud; Hutter, Frank

Weight-Entanglement Meets Gradient-Based Neural Architecture Search Technical Report

2023.

2384.

Chen, Tianyi; Ding, Tianyu; Zhu, Zhihui; Chen, Zeyu; Wu, HsiangTao; Zharkov, Ilya; Liang, Luming

OTOv3: Automatic Architecture-Agnostic Neural Network Training and Compression from Structured Pruning to Erasing Operators Technical Report

2023.

2383.

Castillo, Angela; Kohler, Jonas; Pérez, Juan C.; Pérez, Juan Pablo; Pumarola, Albert; Ghanem, Bernard; Arbeláez, Pablo; Thabet, Ali

Adaptive Guidance: Training-free Acceleration of Conditional Diffusion Models Technical Report

2023.

2382.

Chopra, Jatin; Kumar, Gaddam Prathik; Ghosh, Archismita; Prasad, Paarth; Vats, Shreya

A Novel Approach to Human Activity Recognition: Integrating Automated Machine Learning and Multimodal Fusion Mechanisms Journal Article

In: International Journal for Research Trends and Innovation, vol. 8, pp. 6, 2023.

2381.

Zhang, Mengxuan; Liu, Long; Jin, Yaochu; Lei, Zhikun; Wang, Zhigang; Jiao, Licheng

Tree-shaped multiobjective evolutionary CNN for hyperspectral image classification Journal Article

In: Applied Soft Computing, pp. 111176, 2023, ISSN: 1568-4946.

Abstract | Links | BibTeX

@article{ZHANG2023111176,

title = {Tree-shaped multiobjective evolutionary CNN for hyperspectral image classification},

author = {Mengxuan Zhang and Long Liu and Yaochu Jin and Zhikun Lei and Zhigang Wang and Licheng Jiao},

url = {https://www.sciencedirect.com/science/article/pii/S1568494623011948},

doi = {https://doi.org/10.1016/j.asoc.2023.111176},

issn = {1568-4946},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

journal = {Applied Soft Computing},

pages = {111176},

abstract = {Convolutional neural networks (CNNs) have achieved significant performances in hyperspectral image (HSI) classification in recent years. However, designing a high-performance CNN depends on human expertise heavily, which usually takes considerable time and labor. With regard to reducing the burden of designing the networks, neural architecture search (NAS) has attracted increasing attention. A typical NAS approach aims to optimize the network architectures in a predefined search space with a suitable search algorithm automatically. However, the existing NAS work does not fully consider the spatial resolution and the spectral noise interference of HSIs. Furthermore, most NAS approaches use sequential blocks or cells to construct the networks, which are unsuitable for extracting multiscale features of HSIs and result in degraded performance. Considering the above challenges, we propose a tree-shaped multiobjective evolutionary CNN (TMOE-CNN) for HSI classification. An expanded search space is designed, which includes the image patch size and the channel number of the input image patches. A multibranch supernetwork structure is proposed, which resembles a tree as the fundamental architecture for the network block. The image patch size and the denoising strength of the input image patches can be established adaptively throughout the evolutionary search process. The tree-shaped networks can fuse multiscale features to enhance the capacity of the network for feature extraction. Additionally, we consider both the classification accuracy and the floating-point computational complexity in the environmental selection. It is helpful to find the networks with simple structure and low complexity while ensuring classification accuracy. Experiments on different HSI datasets show that TMOE-CNN can search CNNs with high accuracies and simple structures automatically.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

2380.

He, Hongyi; Liu, Longjun; Zhang, Haonan; Zheng, Nanning

IS-DARTS: Stabilizing DARTS through Precise Measurement on Candidate Importance Technical Report

2023.

2379.

Sridhar, Sharath Nittur; Szankin, Maciej; Chen, Fang; Sundaresan, Sairam; Sarah, Anthony

SimQ-NAS: Simultaneous Quantization Policy and Neural Architecture Search Technical Report

2023.

2378.

Zhang, Zitong; Liu, Zhicheng; Zhao, Yunfeng; Qiu, Chao; Zhang, Cheng; Wang, Xiaofei

ENASFL: A Federated Neural Architecture Search Scheme for Heterogeneous Deep Models in Distributed Edge Computing Systems Journal Article

In: IEEE Transactions on Network Science and Engineering, pp. 1-11, 2023.

2377.

Chen, Tianyi; Liang, Luming; Ding, Tianyu; Zharkov, Ilya

OTOv3: Towards Automatic Sub-Network Search Within General Super Deep Neural Networks Miscellaneous

2023.

2376.

Lanjewar, Madhusudan G; Panchbhai, Kamini G

Enhancing Fish Freshness Prediction using NasNet-LSTM Journal Article

In: Journal of Food Composition and Analysis, pp. 105945, 2023, ISSN: 0889-1575.

Abstract | Links | BibTeX

2375.

Xie, Tao; Dai, Kun; Jiang, Zhiqiang; Li, Ruifeng; Mao, Shouren; Wang, Ke; Zhao, Lijun

ViT-MVT: A Unified Vision Transformer Network for Multiple Vision Tasks Journal Article

In: IEEE Transactions on Neural Networks and Learning Systems, pp. 1-15, 2023.

2374.

Tu, Chongjun; Ye, Peng; Lin, Weihao; Ye, Hancheng; Yu, Chong; Chen, Tao; Li, Baopu; Ouyang, Wanli

Efficient Architecture Search via Bi-level Data Pruning Technical Report

2023.

2373.

Wu, Xuan; Wang, Di; Chen, Huanhuan; Yan, Lele; Xiao, Yubin; Miao, Chunyan; Ge, Hongwei; Xu, Dong; Liang, Yanchun; Wang, Kangping; Wu, Chunguo; Zhou, You

Neural Architecture Search for Text Classification With Limited Computing Resources Using Efficient Cartesian Genetic Programming Journal Article

In: IEEE Transactions on Evolutionary Computation, pp. 1-1, 2023.

2372.

Wen, Yingpeng; Yu, Weijiang; Zheng, Fudan; Huang, Dan; Xiao, Nong

AdaNAS: Adaptively Post-processing with Self-supervised Neural Architecture Search for Ensemble Rainfall Forecasts Technical Report

2023.

2371.

Sun, Haiyang; Lian, Zheng; Sun, Licai; Liu, Bin; Tao, Jianhua

RMNAS: A Multimodal Neural Architecture Search Framework For Robust Multimodal Sentiment Analysis Technical Report

2023.

2370.

Zhou, Xun; Wang, Zhenkun; Feng, Liang; Liu, Songbai; Wong, Ka-Chun; Tan, Kay Chen

Towards Evolutionary Multi-Task Convolutional Neural Architecture Search Journal Article

In: IEEE Transactions on Evolutionary Computation, pp. 1-1, 2023.

2369.

Leal, Daivid V.; Araujo, Israel F.; Silva, Adenilton J.

Training and meta-training an ensemble of binary neural networks with quantum computing Journal Article

In: Neurocomputing, pp. 127169, 2023, ISSN: 0925-2312.

Abstract | Links | BibTeX

2368.

Khare, Alind; Garg, Dhruv; Kalra, Sukrit; Grandhi, Snigdha; Stoica, Ion; Tumanov, Alexey

SuperServe: Fine-Grained Inference Serving for Unpredictable Workloads Technical Report

2023.

2367.

Zhang, Mengxuan; Liu, Long; Lei, Zhikun; Ma, Kun; Feng, Jie; Liu, Zhao; Jiao, Licheng

Multi-Scale Spatial-Channel Transformer Architecture Search for Remote Sensing Image Change Detection Journal Article

In: IEEE Geoscience and Remote Sensing Letters, pp. 1-1, 2023.

2366.

Zhang, Fangyu; Pan, Yi; Wei, Yanjie; Liu, Jin; Lin, Zhenli

A Heuristic Sparsification Method to Improve the Performance of Neural Networks on Autism Spectrum Disorder Identification Tasks Proceedings Article

In: 2023 13th International Conference on Information Science and Technology (ICIST), pp. 1-8, 2023.

2365.

Gong, Cheng; Nan, Yang; Pang, Lie Meng; Ishibuchi, Hisao; Zhang, Qingfu

Examination of the Multimodal Nature of Multi-Objective Neural Architecture Search Proceedings Article

In: 2023 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1821-1828, 2023.

2364.

Londt, Trevor; Gao, Xiaoying; Andreae, Peter; Mei, Yi

A Two-Stage Hybrid GA-Cellular Encoding Approach to Neural Architecture Search Proceedings Article

In: 2023 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1814-1820, 2023.

2363.

Meng, Lingtong; Chen, Yuting

DFairNAS: A Dataflow Fairness Approach to Training NAS Neural Networks Proceedings Article

In: 2023 16th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), pp. 1-6, 2023.

2362.

Ser, Javier Del; Andrés, Alain; Bilbao, Miren Nekane; Laña, Ibai; Lobo, Jesus L.

Evolutionary Multi-Objective Quantization of Randomization-Based Neural Networks Proceedings Article

In: 2023 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1346-1351, 2023.

2361.

Thakur, Aditya Shankar; Awari, Akshar Bajrang; Lyu, Zimeng; Desell, Travis

Efficient Neuroevolution Using Island Repopulation and Simplex Hyperparameter Optimization Proceedings Article

In: 2023 IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1837-1842, 2023.

2360.

Sari, Marlindia Ike; Ibnugraha, Prajna Deshanta; Sani, Muhammad Ikhsan; Rizal, Moch Fahru; Hanifa, Fanni Husnul; Kurniawan, Aris Pujud

Initial Estimation Passenger Number using YOLO-NAS Proceedings Article

In: 2023 International Conference on Artificial Intelligence, Blockchain, Cloud Computing, and Data Analytics (ICoABCD), pp. 181-185, 2023.

2359.

Wang, Xingyu; Ji, Junzhong

Adaptive particle swarm architecture search based on multi-level convolutions for functional brain network classification Proceedings Article

In: 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 654-659, 2023.

2358.

Chen, Shijie; Chen, Shengbo; Lei, Zhou

RGA-Reid: Neural Architecture Search Based on Relation-Aware Global Attention for Person Re-Identification Proceedings Article

In: 2023 IEEE 11th Joint International Information Technology and Artificial Intelligence Conference (ITAIC), pp. 399-402, 2023.

2357.

Li, Jianbo; Hou, Guirong; Xiang, Hong; Lei, Zhiwen; Chen, Shaomiao

An efficient neural architecture search based deep learning algorithm for surface defects detection of T-beam Journal Article

In: International Journal of Embedded Systems, vol. 16, no. 2, pp. 153-160, 2023.

Abstract | Links | BibTeX

2356.

Zhang, Tian; Li, Nan; Zhou, Yuee; Cai, Wei; Ma, Lianbo

Information extraction of Chinese medical electronic records via evolutionary neural architecture search Proceedings Article

In: 2023 IEEE International Conference on Data Mining Workshops (ICDMW), pp. 396-405, 2023.

2355.

Tian, Wensheng; Zhang, Lei; Chen, Shuangxi; Wang, Hu; Luo, Xiao

Work-in-Progress: Model Dependability Constrained Differentiable Architecture Search for Safety Critical DNN Tasks Proceedings Article

In: 2023 IEEE Real-Time Systems Symposium (RTSS), pp. 447-450, 2023.

2354.

Minimizing the weight uncertainty in Neural Networks Using Bayesian Optimization Proceedings Article

In: 2023 7th International Conference on Electronics, Materials Engineering & Nano-Technology (IEMENTech), pp. 1-6, 2023.

2353.

Wang, Qinsi; Ke, Jinghan; Liang, Zhi; Zhang, Sihai

MathNAS: If Blocks Have a Role in Mathematical Architecture Design Proceedings Article

In: Oh, Alice; Naumann, Tristan; Globerson, Amir; Saenko, Kate; Hardt, Moritz; Levine, Sergey (Ed.): Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023, 2023.

2352.

Anand, R N; Singh, Rimjhim Padam; Gupta, Deepa; Palaniappan, Kannappan

Ship Detection in Satellite Images using You Only Look Once-Neural Architecture Search Proceedings Article

In: 2023 9th International Conference on Signal Processing and Communication (ICSC), pp. 463-468, 2023.

2351.

Sarti, Simone; Lomurno, Eugenio; Matteucci, Matteo

Neural Architecture Transfer 2: A Paradigm for Improving Efficiency in Multi-Objective Neural Architecture Search Technical Report

2023.

2350.

Mandal, Murari; Meedimale, Yashwanth Reddy; Reddy, M. Satish Kumar; Vipparthi, Santosh Kumar

Neural Architecture Search for Image Dehazing Journal Article

In: IEEE Transactions on Artificial Intelligence, vol. 4, no. 5, pp. 1337-1347, 2023.

2022

2349.

Yan, Shen

New Perspectives in Neural Architecture Search: Architecture Embeddings, Efficient Performance Estimations, and Their Applications PhD Thesis

2022.

2348.

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

Neural predictor-based automated graph classifier framework Journal Article

In: Machine Learning, 2022.

2347.

Wei, Fang; Zhenhao, Zhu; Zhou, Hong; Tao, Zhang; Jun, Sun; Xiaojun, Wu

Efficient automatically evolving convolutional neural network for image denoising Journal Article

In: Memetic Computing , 2022.

2346.

Men, Yanger; Li, Jingtao

Image Steganography of convolutional neural network based on neural architecture search Technical Manual

2022.

2345.

Fan, Liang; Wang, Handing

Surrogate-assisted evolutionary neural architecture search with network embedding Journal Article

In: Complex & Intelligent Systems (2022), 2022.

2344.

Hou, Libin; Wang, Linyuan; Peng, Qi; Yan, Bin

Stochastic Gradient Estimator for Differentiable NAS Proceedings Article

In: OPT2022: 14th Annual Workshop on Optimization for Machine Learning, 2022.

2343.

Torabi, Ali; Sharifi, Arash; Teshnehlab, Mohammad

Using Cartesian Genetic Programming Approach with New Crossover Technique to Design Convolutional Neural Networks Journal Article

In: Neural Processing Letters, 2022.

2342.

Wang, Chunnan; Zhang, Kaixin; Wang, Hongzhi; Chen, Bozhou

Auto-STGCN: Autonomous Spatial-Temporal Graph Convolutional Network Search Journal Article

In: ACM Trans. Knowl. Discov. Data, 2022, ISSN: 1556-4681, (Just Accepted).

Abstract | Links | BibTeX

@article{10.1145/3571285,

title = {Auto-STGCN: Autonomous Spatial-Temporal Graph Convolutional Network Search},

author = {Chunnan Wang and Kaixin Zhang and Hongzhi Wang and Bozhou Chen},

url = {https://doi.org/10.1145/3571285},

doi = {10.1145/3571285},

issn = {1556-4681},

year  = {2022},

date = {2022-12-01},

urldate = {2022-12-01},

journal = {ACM Trans. Knowl. Discov. Data},

publisher = {Association for Computing Machinery},

address = {New York, NY, USA},

abstract = {In recent years, many spatial-temporal graph convolutional network (STGCN) models are proposed to deal with the spatial-temporal network data forecasting problem. These STGCN models have their own advantages, i.e., each of them puts forward many effective operations and achieves good prediction results in the real applications. If users can effectively utilize and combine these excellent operations integrating the advantages of existing models, then they may obtain more effective STGCN models thus create greater value using existing work. However, they fail to do so due to the lack of domain knowledge, and there is lack of automated system to help users to achieve this goal. In this paper, we fill this gap and propose Auto-STGCN algorithm, which makes use of existing models to automatically explore high-performance STGCN model for specific scenarios. Specifically, we design Unified-STGCN framework, which summarizes the operations of existing architectures, and use parameters to control the usage and characteristic attributes of each operation, so as to realize the parameterized representation of the STGCN architecture and the reorganization and fusion of advantages. Then, we present Auto-STGCN, an optimization method based on reinforcement learning, to quickly search the parameter search space provided by Unified-STGCN, and generate optimal STGCN models automatically. Extensive experiments on real-world benchmark datasets show that our Auto-STGCN can find STGCN models superior to existing STGCN models used for search space construction, which demonstrates the effectiveness of our proposed method.},

note = {Just Accepted},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

4191 entries « ‹ 37 of 84 › »