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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
DataDAM: Efficient Dataset Distillation with Attention MatchingCode1
Dataset Condensation with Distribution MatchingCode1
Bag of Baselines for Multi-objective Joint Neural Architecture Search and Hyperparameter OptimizationCode1
Journey Towards Tiny Perceptual Super-ResolutionCode1
Efficient Neural Architecture Search for End-to-end Speech Recognition via Straight-Through GradientsCode1
AutoInit: Analytic Signal-Preserving Weight Initialization for Neural NetworksCode1
AutoKE: An automatic knowledge embedding framework for scientific machine learningCode1
Accelerating Neural Architecture Search via Proxy DataCode1
Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree SearchCode1
Learning Versatile Neural Architectures by Propagating Network CodesCode1
EH-DNAS: End-to-End Hardware-aware Differentiable Neural Architecture SearchCode1
Enhancing Neural Architecture Search with Multiple Hardware Constraints for Deep Learning Model Deployment on Tiny IoT DevicesCode1
Differentiable Neural Architecture Search for Extremely Lightweight Image Super-ResolutionCode1
Automated Graph Machine Learning: Approaches, Libraries, Benchmarks and DirectionsCode1
AutoSpeech: Neural Architecture Search for Speaker RecognitionCode1
Automated Machine Learning on Graphs: A SurveyCode1
Deep Multimodal Neural Architecture SearchCode1
Local Search is a Remarkably Strong Baseline for Neural Architecture 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
Memory-Efficient Hierarchical Neural Architecture Search for Image RestorationCode1
DSNAS: Direct Neural Architecture Search without Parameter RetrainingCode1
deepstruct -- linking deep learning and graph theoryCode1
Automatic Relation-aware Graph Network ProliferationCode1
DEHB: Evolutionary Hyperband for Scalable, Robust and Efficient Hyperparameter OptimizationCode1
AdvRush: Searching for Adversarially Robust Neural ArchitecturesCode1
Efficient Forward Architecture SearchCode1
AOWS: Adaptive and optimal network width search with latency constraintsCode1
AutoML4ETC: Automated Neural Architecture Search for Real-World Encrypted Traffic ClassificationCode1
Designing Novel Cognitive Diagnosis Models via Evolutionary Multi-Objective Neural Architecture SearchCode1
AutoML: A Survey of the State-of-the-ArtCode1
Designing the Topology of Graph Neural Networks: A Novel Feature Fusion PerspectiveCode1
MSINet: Twins Contrastive Search of Multi-Scale Interaction for Object ReIDCode1
DHP: Differentiable Meta Pruning via HyperNetworksCode1
AutoMoE: Heterogeneous Mixture-of-Experts with Adaptive Computation for Efficient Neural Machine TranslationCode1
Differentiable Model Scaling using Differentiable TopkCode1
AutoSTR: Efficient Backbone Search for Scene Text RecognitionCode1
Efficient Hyperparameter Optimization with Adaptive Fidelity IdentificationCode1
NAS-Bench-101: Towards Reproducible Neural Architecture SearchCode1
AutoPEFT: Automatic Configuration Search for Parameter-Efficient Fine-TuningCode1
Angle-based Search Space Shrinking for Neural Architecture SearchCode1
DiffusionNAG: Predictor-guided Neural Architecture Generation with Diffusion ModelsCode1
Surrogate NAS Benchmarks: Going Beyond the Limited Search Spaces of Tabular NAS BenchmarksCode1
EAGAN: Efficient Two-stage Evolutionary Architecture Search for GANsCode1
Discretization-Aware Architecture SearchCode1
Does Unsupervised Architecture Representation Learning Help Neural Architecture Search?Code1
AutoReCon: Neural Architecture Search-based Reconstruction for Data-free CompressionCode1
NAS-BNN: Neural Architecture Search for Binary Neural NetworksCode1
EEEA-Net: An Early Exit Evolutionary Neural Architecture SearchCode1
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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