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 1501–1550 of 1915 papers

TitleStatusHype
Auto-ReID: Searching for a Part-aware ConvNet for Person Re-IdentificationCode0
CSCO: Connectivity Search of Convolutional OperatorsCode0
EENA: Efficient Evolution of Neural ArchitectureCode0
TART: Token-based Architecture Transformer for Neural Network Performance PredictionCode0
ImmuNetNAS: An Immune-network approach for searching Convolutional Neural Network ArchitecturesCode0
Implantable Adaptive Cells: differentiable architecture search to improve the performance of any trained U-shaped networkCode0
CR-LSO: Convex Neural Architecture Optimization in the Latent Space of Graph Variational Autoencoder with Input Convex Neural NetworksCode0
Improved Differentiable Architecture Search for Language Modeling and Named Entity RecognitionCode0
Improve Ranking Correlation of Super-net through Training Scheme from One-shot NAS to Few-shot NASCode0
AutoPose: Searching Multi-Scale Branch Aggregation for Pose EstimationCode0
Arch-Graph: Acyclic Architecture Relation Predictor for Task-Transferable Neural Architecture SearchCode0
ReFusion: Improving Natural Language Understanding with Computation-Efficient Retrieval Representation FusionCode0
Improving Neural Architecture Search by Mixing a FireFly algorithm with a Training Free EvaluationCode0
Improving Neural Architecture Search Image Classifiers via Ensemble LearningCode0
Improving Neural Networks for Time Series Forecasting using Data Augmentation and AutoMLCode0
Cream of the Crop: Distilling Prioritized Paths For One-Shot Neural Architecture SearchCode0
Improving Random-Sampling Neural Architecture Search by Evolving the Proxy Search SpaceCode0
Improving Ranking Correlation of Supernet with Candidates Enhancement and Progressive TrainingCode0
Posterior-Guided Neural Architecture SearchCode0
Autoequivariant Network Search via Group DecompositionCode0
Improving the Efficient Neural Architecture Search via Rewarding ModificationsCode0
One-Shot Neural Architecture Search via Compressive SensingCode0
Improving the sample-efficiency of neural architecture search with reinforcement learningCode0
One-Shot Neural Architecture Search via Self-Evaluated Template NetworkCode0
AutonoML: Towards an Integrated Framework for Autonomous Machine LearningCode0
GreenMachine: Automatic Design of Zero-Cost Proxies for Energy-Efficient NASCode0
Contrastive Self-supervised Neural Architecture SearchCode0
Continuous Cartesian Genetic Programming based representation for Multi-Objective Neural Architecture SearchCode0
The CoSTAR Block Stacking Dataset: Learning with Workspace ConstraintsCode0
Inner Ensemble Networks: Average Ensemble as an Effective RegularizerCode0
Insights from the Use of Previously Unseen Neural Architecture Search DatasetsCode0
InstaNAS: Instance-aware Neural Architecture SearchCode0
Continual and Multi-Task Architecture SearchCode0
Task-Aware Neural Architecture SearchCode0
GraphPAS: Parallel Architecture Search for Graph Neural NetworksCode0
On Redundancy and Diversity in Cell-based Neural Architecture SearchCode0
On Spectrogram Analysis in a Multiple Classifier Fusion Framework for Power Grid Classification Using Electric Network FrequencyCode0
Inter-layer Transition in Neural Architecture SearchCode0
On the Adversarial Transferability of Generalized "Skip Connections"Code0
Interpretable neural architecture search and transfer learning for understanding CRISPR/Cas9 off-target enzymatic reactionsCode0
Auto-nnU-Net: Towards Automated Medical Image SegmentationCode0
TAS: Ternarized Neural Architecture Search for Resource-Constrained Edge DevicesCode0
Training-free Neural Architecture Search through Variance of Knowledge of Deep Network WeightsCode0
Investigating the Impact of Hard Samples on Accuracy Reveals In-class Data ImbalanceCode0
BINAS: Bilinear Interpretable Neural Architecture SearchCode0
i-Razor: A Differentiable Neural Input Razor for Feature Selection and Dimension Search in DNN-Based Recommender SystemsCode0
IRLAS: Inverse Reinforcement Learning for Architecture SearchCode0
GraphNAS: Graph Neural Architecture Search with Reinforcement LearningCode0
CONetV2: Efficient Auto-Channel Size Optimization for CNNsCode0
On the Security Risks of AutoMLCode0
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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-RDARTS-L2Accuracy (Test)46.71—Unverified
4β-SDARTS-RSAccuracy (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
7NN-MASS- CIFAR-ATop-1 Error Rate3—Unverified
8DARTS (first order)Top-1 Error Rate3—Unverified
9NASGEPTop-1 Error Rate2.82—Unverified
10AlphaX-1 (cutout NASNet)Top-1 Error Rate2.82—Unverified