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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 201–250 of 1915 papers

TitleStatusHype
HKNAS: Classification of Hyperspectral Imagery Based on Hyper Kernel Neural Architecture SearchCode1
HR-NAS: Searching Efficient High-Resolution Neural Architectures with Lightweight TransformersCode1
ConvNet Architecture Search for Spatiotemporal Feature LearningCode1
Hyper-Representations as Generative Models: Sampling Unseen Neural Network WeightsCode1
DARTS: Differentiable Architecture SearchCode1
AutoInit: Analytic Signal-Preserving Weight Initialization for Neural NetworksCode1
DC-BENCH: Dataset Condensation BenchmarkCode1
Accelerating Neural Architecture Search via Proxy DataCode1
Memory-Efficient Hierarchical Neural Architecture Search for Image DenoisingCode1
ISNAS-DIP: Image-Specific Neural Architecture Search for Deep Image PriorCode1
ColdNAS: Search to Modulate for User Cold-Start RecommendationCode1
AdvRush: Searching for Adversarially Robust Neural ArchitecturesCode1
Knapsack Pruning with Inner DistillationCode1
Automated Graph Machine Learning: Approaches, Libraries, Benchmarks and DirectionsCode1
Discovering Neural WiringsCode1
Automated Machine Learning on Graphs: A SurveyCode1
BM-NAS: Bilevel Multimodal Neural Architecture SearchCode1
Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree SearchCode1
Automated Model Design and Benchmarking of 3D Deep Learning Models for COVID-19 Detection with Chest CT ScansCode1
An Asymptotically Optimal Multi-Armed Bandit Algorithm and Hyperparameter OptimizationCode1
Automated Search for Resource-Efficient Branched Multi-Task NetworksCode1
BN-NAS: Neural Architecture Search with Batch NormalizationCode1
AOWS: Adaptive and optimal network width search with latency constraintsCode1
Can GPT-4 Perform Neural Architecture Search?Code1
Automatic Relation-aware Graph Network ProliferationCode1
Exploring the Loss Landscape in Neural Architecture SearchCode1
Memory-Efficient Hierarchical Neural Architecture Search for Image RestorationCode1
Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed SpacesCode1
Meta-prediction Model for Distillation-Aware NAS on Unseen DatasetsCode1
AutoML4ETC: Automated Neural Architecture Search for Real-World Encrypted Traffic ClassificationCode1
MixPath: A Unified Approach for One-shot Neural Architecture SearchCode1
AutoML: A Survey of the State-of-the-ArtCode1
CM-NAS: Cross-Modality Neural Architecture Search for Visible-Infrared Person Re-IdentificationCode1
Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-ResolutionCode1
CATE: Computation-aware Neural Architecture Encoding with TransformersCode1
AutoMoE: Heterogeneous Mixture-of-Experts with Adaptive Computation for Efficient Neural Machine TranslationCode1
MPCViT: Searching for Accurate and Efficient MPC-Friendly Vision Transformer with Heterogeneous AttentionCode1
MSINet: Twins Contrastive Search of Multi-Scale Interaction for Object ReIDCode1
Multi-objective Differentiable Neural Architecture SearchCode1
Multi-objective Optimization by Learning Space PartitionsCode1
AutoPEFT: Automatic Configuration Search for Parameter-Efficient Fine-TuningCode1
Angle-based Search Space Shrinking for Neural Architecture SearchCode1
NAS-Bench-201: Extending the Scope of Reproducible Neural Architecture SearchCode1
NAS-Bench-1Shot1: Benchmarking and Dissecting One-shot Neural Architecture SearchCode1
Canvas: End-to-End Kernel Architecture Search in Neural NetworksCode1
NAS-Bench-360: Benchmarking Neural Architecture Search on Diverse TasksCode1
CAKES: Channel-wise Automatic KErnel Shrinking for Efficient 3D NetworksCode1
AutoReCon: Neural Architecture Search-based Reconstruction for Data-free CompressionCode1
NAS-DIP: Learning Deep Image Prior with Neural Architecture SearchCode1
ChamNet: Towards Efficient Network Design through Platform-Aware Model AdaptationCode1
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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
5NARAccuracy (Test)46.66—Unverified
6ASE-NAS+Accuracy (Val)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