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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1226–1250 of 1915 papers

TitleStatusHype
Homogeneous Architecture Augmentation for Neural PredictorCode0
MFAGAN: A Compression Framework for Memory-Efficient On-Device Super-Resolution GAN—0
Experiments on Properties of Hidden Structures of Sparse Neural NetworksCode0
μDARTS: Model Uncertainty-Aware Differentiable Architecture Search—0
LENS: Layer Distribution Enabled Neural Architecture Search in Edge-Cloud Hierarchies—0
A Novel Evolutionary Algorithm for Hierarchical Neural Architecture SearchCode0
Federated Whole Prostate Segmentation in MRI with Personalized Neural Architectures—0
Scene-adaptive Knowledge Distillation for Sequential Recommendation via Differentiable Architecture Search—0
AutoBERT-Zero: Evolving BERT Backbone from Scratch—0
Neural Architecture Search using Covariance Matrix Adaptation Evolution Strategy—0
LANA: Latency Aware Network Acceleration—0
Core-set Sampling for Efficient Neural Architecture Search—0
Bag of Tricks for Neural Architecture Search—0
Does Form Follow Function? An Empirical Exploration of the Impact of Deep Neural Network Architecture Design on Hardware-Specific Acceleration—0
Uncertainty Modeling of Emerging Device-based Computing-in-Memory Neural Accelerators with Application to Neural Architecture Search—0
Mutation is all you need—0
CHASE: Robust Visual Tracking via Cell-Level Differentiable Neural Architecture SearchCode0
Exploring Robust Architectures for Deep Artificial Neural NetworksCode0
Poisoning the Search Space in Neural Architecture Search—0
AutoAdapt: Automated Segmentation Network Search for Unsupervised Domain Adaptation—0
NAX: Co-Designing Neural Network and Hardware Architecture for Memristive Xbar based Computing Systems—0
Bayesian Deep Learning Hyperparameter Search for Robust Function Mapping to Polynomials with Noise—0
Latency-Aware Neural Architecture Search with Multi-Objective Bayesian Optimization—0
Connection Sensitivity Matters for Training-free DARTS: From Architecture-Level Scoring to Operation-Level Sensitivity Analysis—0
DARTS-PRIME: Regularization and Scheduling Improve Constrained Optimization in Differentiable NAS—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-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