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Hierarchical Representations for Efficient Architecture Search

arXiv 1711.00436 ↗First posted 1 Nov 2017cs.LG cs.CV cs.NEcited by 188

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Abstract (arXiv)

We explore efficient neural architecture search methods and show that a simple yet powerful evolutionary algorithm can discover new architectures with excellent performance. Our approach combines a novel hierarchical genetic representation scheme that imitates the modularized design pattern commonly adopted by human experts, and an expressive search space that supports complex topologies. Our algorithm efficiently discovers architectures that outperform a large number of manually designed models for image classification, obtaining top-1 error of 3.6% on CIFAR-10 and 20.3% when transferred to ImageNet, which is competitive with the best existing neural architecture search approaches. We also present results using random search, achieving 0.3% less top-1 accuracy on CIFAR-10 and 0.1% less on ImageNet whilst reducing the search time from 36 hours down to 1 hour.

Key facts. Cited by 188 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Nov 2017.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 73; 2022: 52; 2023: 32; 2024: 21; 2025: 7; 2026: 3.

188 papers.

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  1. 2021Primer: Searching for Efficient Transformers for Language Modelingcited by 162
  2. 2023Neural Architecture Search: Insights from 1000 Paperscited by 136
  3. 2021Rethinking Architecture Selection in Differentiable NAScited by 92
  4. 2023Full Stack Optimization of Transformer Inference: a Surveycited by 79
  5. 2021Partial Is Better Than All: Revisiting Fine-tuning Strategy for Few-shot Learningcited by 72
  6. 2023ZiCo: Zero-shot NAS via Inverse Coefficient of Variation on Gradientscited by 57
  7. 2023CktGNN: Circuit Graph Neural Network for Electronic Design Automationcited by 55
  8. 2021Neural Feature Search for RGB-Infrared Person Re-Identificationcited by 50
  9. 2021Global2Local: Efficient Structure Search for Video Action Segmentationcited by 42
  10. 2022Low-rank lottery tickets: finding efficient low-rank neural networks via matrix differential equationscited by 42
  11. 2022Multi-Objective Hyperparameter Optimization in Machine Learning -- An Overviewcited by 37
  12. 2021Contrastive Neural Architecture Search with Neural Architecture Comparatorscited by 33
38 more
  1. 2022Enable Deep Learning on Mobile Devices: Methods, Systems, and Applicationscited by 32
  2. 2021Towards Improving the Consistency, Efficiency, and Flexibility of Differentiable Neural Architecture Searchcited by 27
  3. 2021Rethinking Graph Neural Architecture Search from Message-passingcited by 26
  4. 2021Core-set Sampling for Efficient Neural Architecture Searchcited by 23
  5. 2023ChatGPT as your Personal Data Scientistcited by 22
  6. 2021CATE: Computation-aware Neural Architecture Encoding with Transformerscited by 21
  7. 2021PSViT: Better Vision Transformer via Token Pooling and Attention Sharingcited by 21
  8. 2023Zero-Shot Neural Architecture Search: Challenges, Solutions, and Opportunitiescited by 21
  9. 2021DPNAS: Neural Architecture Search for Deep Learning with Differential Privacycited by 20
  10. 2022PACE: A Parallelizable Computation Encoder for Directed Acyclic Graphscited by 20
  11. 2026Towards Execution-Grounded Automated AI Researchcited by 19
  12. 2022Lite Pose: Efficient Architecture Design for 2D Human Pose Estimationcited by 16
  13. 2023MSINet: Twins Contrastive Search of Multi-Scale Interaction for Object ReIDcited by 16
  14. 2023TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphscited by 16
  15. 2021Sphynx: ReLU-Efficient Network Design for Private Inferencecited by 15
  16. 2021Latency-Aware Neural Architecture Search with Multi-Objective Bayesian Optimizationcited by 15
  17. 2022Generalization Properties of NAS under Activation and Skip Connection Searchcited by 14
  18. 2023Computation-efficient Deep Learning for Computer Vision: A Surveycited by 14
  19. 2021Memory-Efficient Differentiable Transformer Architecture Searchcited by 13
  20. 2021Neural Architecture Dilation for Adversarial Robustnesscited by 13
  21. 2022A Survey on Computationally Efficient Neural Architecture Searchcited by 12
  22. 2023Robust low-rank training via approximate orthonormal constraintscited by 12
  23. 2021Multi-objective Search of Robust Neural Architectures against Multiple Types of Adversarial Attackscited by 11
  24. 2022Neural Architecture Search for Dense Prediction Tasks in Computer Visioncited by 11
  25. 2021iDARTS: Improving DARTS by Node Normalization and Decorrelation Discretizationcited by 10
  26. 2021JUWELS Booster -- A Supercomputer for Large-Scale AI Researchcited by 10
  27. 2022RF-Next: Efficient Receptive Field Search for Convolutional Neural Networkscited by 10
  28. 2022Automatic and effective discovery of quantum kernelscited by 10
  29. 2021VRoC: Variational Autoencoder-aided Multi-task Rumor Classifier Based on Textcited by 9
  30. 2021Reconsidering CO2 emissions from Computer Visioncited by 9
  31. 2021Accelerating Evolutionary Neural Architecture Search via Multi-Fidelity Evaluationcited by 9
  32. 2021EEEA-Net: An Early Exit Evolutionary Neural Architecture Searchcited by 9
  33. 2022MLP-3D: A MLP-like 3D Architecture with Grouped Time Mixingcited by 9
  34. 2022Slimmable Domain Adaptationcited by 9
  35. 2022Construction of Hierarchical Neural Architecture Search Spaces based on Context-free Grammarscited by 9
  36. 2022A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithmscited by 8
  37. 2023Enabling Resource-efficient AIoT System with Cross-level Optimization: A surveycited by 8
  38. 2021Fisher Task Distance and Its Application in Neural Architecture Searchcited by 7

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