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 1101–1125 of 1915 papers

TitleStatusHype
Proxyless Neural Architecture Adaptation for Supervised Learning and Self-Supervised Learning—0
Pruning Compact ConvNets for Efficient Inference—0
PSE-Net: Channel Pruning for Convolutional Neural Networks with Parallel-subnets Estimator—0
Pushing Joint Image Denoising and Classification to the Edge—0
Puzzle: Distillation-Based NAS for Inference-Optimized LLMs—0
PVNAS: 3D Neural Architecture Search with Point-Voxel Convolution—0
PV-NAS: Practical Neural Architecture Search for Video Recognition—0
Pyramid Architecture Search for Real-Time Image Deblurring—0
QuadraNet: Improving High-Order Neural Interaction Efficiency with Hardware-Aware Quadratic Neural Networks—0
Quantifying uncertainty for deep learning based forecasting and flow-reconstruction using neural architecture search ensembles—0
Quantum Architecture Search with Unsupervised Representation Learning—0
Quantum Neural Architecture Search with Quantum Circuits Metric and Bayesian Optimization—0
Quasi-orthogonality and intrinsic dimensions as measures of learning and generalisation—0
Qubit-Wise Architecture Search Method for Variational Quantum Circuits—0
QuMoS: A Framework for Preserving Security of Quantum Machine Learning Model—0
RADARS: Memory Efficient Reinforcement Learning Aided Differentiable Neural Architecture Search—0
RandomNet: Towards Fully Automatic Neural Architecture Design for Multimodal Learning—0
Ranking Architectures by Feature Extraction Capabilities—0
Ranking architectures using meta-learning—0
Ranking Convolutional Architectures by their Feature Extraction Capabilities—0
Rankitect: Ranking Architecture Search Battling World-class Engineers at Meta Scale—0
RankNAS: Efficient Neural Architecture Search by Pairwise Ranking—0
RANK-NOSH: Efficient Predictor-Based Architecture Search via Non-Uniform Successive Halving—0
RAPDARTS: Resource-Aware Progressive Differentiable Architecture Search—0
Rapid Deployment of DNNs for Edge Computing via Structured Pruning at Initialization—0
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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