SOTAVerified

Neural Architecture Search

Neural architecture search (NAS) is a technique for automating the design of artificial neural networks (ANN), a widely used model in the field of machine learning. NAS essentially takes the process of a human manually tweaking a neural network and learning what works well, and automates this task to discover more complex architectures.

Image Credit : NAS with Reinforcement Learning

Papers

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Showing 401–450 of 1915 papers

TitleStatusHype
Λ-DARTS: Mitigating Performance Collapse by Harmonizing Operation Selection among CellsCode0
Learn Basic Skills and Reuse: Modularized Adaptive Neural Architecture Search (MANAS)Code0
Large Language Model Assisted Adversarial Robustness Neural Architecture SearchCode0
Seesaw-Net: Convolution Neural Network With Uneven Group ConvolutionCode0
AutonoML: Towards an Integrated Framework for Autonomous Machine LearningCode0
Landmark Regularization: Ranking Guided Super-Net Training in Neural Architecture SearchCode0
Large-Scale Evolution of Image ClassifiersCode0
Learning Deep Morphological Networks with Neural Architecture SearchCode0
Learning Implicitly Recurrent CNNs Through Parameter SharingCode0
Auto-nnU-Net: Towards Automated Medical Image SegmentationCode0
ISyNet: Convolutional Neural Networks design for AI acceleratorCode0
IRLAS: Inverse Reinforcement Learning for Architecture SearchCode0
i-Razor: A Differentiable Neural Input Razor for Feature Selection and Dimension Search in DNN-Based Recommender SystemsCode0
3DLaneNAS: Neural Architecture Search for Accurate and Light-Weight 3D Lane DetectionCode0
BINAS: Bilinear Interpretable Neural Architecture SearchCode0
IS-DARTS: Stabilizing DARTS through Precise Measurement on Candidate ImportanceCode0
On Adversarial Robustness: A Neural Architecture Search perspectiveCode0
Inter-layer Transition in Neural Architecture SearchCode0
Automating Data Science Pipelines with Tensor CompletionCode0
Automated Dominative Subspace Mining for Efficient Neural Architecture SearchCode0
A Data-driven Approach to Neural Architecture Search InitializationCode0
Interpretable neural architecture search and transfer learning for understanding CRISPR/Cas9 off-target enzymatic reactionsCode0
Insights from the Use of Previously Unseen Neural Architecture Search DatasetsCode0
InstaNAS: Instance-aware Neural Architecture SearchCode0
Improving the sample-efficiency of neural architecture search with reinforcement learningCode0
DCLP: Neural Architecture Predictor with Curriculum Contrastive LearningCode0
Accel-NASBench: Sustainable Benchmarking for Accelerator-Aware NASCode0
Inner Ensemble Networks: Average Ensemble as an Effective RegularizerCode0
Investigating the Impact of Hard Samples on Accuracy Reveals In-class Data ImbalanceCode0
Knowledge-aware Evolutionary Graph Neural Architecture SearchCode0
Learning Interpretable Models Through Multi-Objective Neural Architecture SearchCode0
An Efficient End-to-End 3D Voxel Reconstruction based on Neural Architecture SearchCode0
Data-to-Model Distillation: Data-Efficient Learning FrameworkCode0
Improving Neural Networks for Time Series Forecasting using Data Augmentation and AutoMLCode0
Dataset Condensation with Differentiable Siamese AugmentationCode0
Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture SearchCode0
Improving Neural Architecture Search by Mixing a FireFly algorithm with a Training Free EvaluationCode0
Improving Neural Architecture Search Image Classifiers via Ensemble LearningCode0
Improving Random-Sampling Neural Architecture Search by Evolving the Proxy Search SpaceCode0
DATA: Differentiable ArchiTecture ApproximationCode0
Improved Differentiable Architecture Search for Language Modeling and Named Entity RecognitionCode0
Data Aware Neural Architecture SearchCode0
Implantable Adaptive Cells: differentiable architecture search to improve the performance of any trained U-shaped networkCode0
Improve Ranking Correlation of Super-net through Training Scheme from One-shot NAS to Few-shot NASCode0
Measuring Uncertainty through Bayesian Learning of Deep Neural Network StructureCode0
Automatic Generation of Neural Architecture Search SpacesCode0
Model Input-Output Configuration Search with Embedded Feature Selection for Sensor Time-series and Image ClassificationCode0
Automated Heterogeneous Network learning with Non-Recursive Message PassingCode0
ImmuNetNAS: An Immune-network approach for searching Convolutional Neural Network ArchitecturesCode0
ReFusion: Improving Natural Language Understanding with Computation-Efficient Retrieval Representation FusionCode0
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All datasetsImageNetNAS-Bench-201, ImageNet-16-120CIFAR-10NAS-Bench-201, CIFAR-100NAS-Bench-201, CIFAR-10CIFAR-10 Image ClassificationCIFAR-100NATS-Bench Topology, CIFAR-10NATS-Bench Topology, CIFAR-100NATS-Bench Topology, ImageNet16-120Food-101NAS-Bench-101

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SPOS (ProxylessNAS (GPU) latency)Accuracy75.3—Unverified
2SPOS (FBNet-C latency)Accuracy75.1—Unverified
3SPOS (block search + channel search)Accuracy74.7—Unverified
4MUXNet-xsTop-1 Error Rate33.3—Unverified
5FBNetV2-F1Top-1 Error Rate31.7—Unverified
6LayerNAS-60MTop-1 Error Rate31—Unverified
7NASGEPTop-1 Error Rate29.51—Unverified
8MUXNet-sTop-1 Error Rate28.4—Unverified
9NN-MASS-ATop-1 Error Rate27.1—Unverified
10FBNetV2-F3Top-1 Error Rate26.8—Unverified
#ModelMetricClaimedVerifiedStatus
1CR-LSOAccuracy (Test)46.98—Unverified
2Shapley-NASAccuracy (Test)46.85—Unverified
3β-SDARTS-RSAccuracy (Test)46.71—Unverified
4β-RDARTS-L2Accuracy (Test)46.71—Unverified
5ASE-NAS+Accuracy (Val)46.66—Unverified
6NARAccuracy (Test)46.66—Unverified
7BaLeNAS-TFAccuracy (Test)46.54—Unverified
8AG-NetAccuracy (Test)46.42—Unverified
9Local searchAccuracy (Test)46.38—Unverified
10NASBOTAccuracy (Test)46.37—Unverified
#ModelMetricClaimedVerifiedStatus
1Balanced MixtureAccuracy (% )91.55—Unverified
2GDASTop-1 Error Rate3.4—Unverified
3Bonsai-NetTop-1 Error Rate3.35—Unverified
4Net2 (2)Top-1 Error Rate3.3—Unverified
5μDARTSTop-1 Error Rate3.28—Unverified
6NN-MASS- CIFAR-CTop-1 Error Rate3.18—Unverified
7DARTS (first order)Top-1 Error Rate3—Unverified
8NN-MASS- CIFAR-ATop-1 Error Rate3—Unverified
9AlphaX-1 (cutout NASNet)Top-1 Error Rate2.82—Unverified
10NASGEPTop-1 Error Rate2.82—Unverified