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 1151–1200 of 1915 papers

TitleStatusHype
A-DeepPixBis: Attentional Angular Margin for Face Anti-Spoofing—0
Automated Machine Learning on Graphs: A SurveyCode1
Tiny Adversarial Mulit-Objective Oneshot Neural Architecture Search—0
Improved Automated Machine Learning from Transfer LearningCode0
Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired PerspectiveCode1
HardCoRe-NAS: Hard Constrained diffeRentiable Neural Architecture SearchCode1
Sandwich Batch Normalization: A Drop-In Replacement for Feature Distribution HeterogeneityCode1
A Novel Framework for Neural Architecture Search in the Hill Climbing Domain—0
Ps and Qs: Quantization-aware pruning for efficient low latency neural network inferenceCode0
Stronger NAS with Weaker PredictorsCode1
Contrastive Self-supervised Neural Architecture SearchCode0
BSQ: Exploring Bit-Level Sparsity for Mixed-Precision Neural Network QuantizationCode1
Towards Accurate and Compact Architectures via Neural Architecture TransformerCode1
Firefly Neural Architecture Descent: a General Approach for Growing Neural NetworksCode1
Rethinking Co-design of Neural Architectures and Hardware Accelerators—0
AlphaNet: Improved Training of Supernets with Alpha-DivergenceCode1
EPE-NAS: Efficient Performance Estimation Without Training for Neural Architecture SearchCode1
Dataset Condensation with Differentiable Siamese AugmentationCode0
Multi-Objective Meta Learning—0
CATE: Computation-aware Neural Architecture Encoding with TransformersCode1
Adversarial Branch Architecture Search for Unsupervised Domain AdaptationCode1
Neural Architecture Search as Program Transformation ExplorationCode1
Regional Attention with Architecture-Rebuilt 3D Network for RGB-D Gesture RecognitionCode1
Searching for Fast Model Families on Datacenter Accelerators—0
Contrastive Embeddings for Neural ArchitecturesCode1
LightSpeech: Lightweight and Fast Text to Speech with Neural Architecture SearchCode1
MUFASA: Multimodal Fusion Architecture Search for Electronic Health Records—0
Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition—0
AACP: Model Compression by Accurate and Automatic Channel Pruning—0
Neural Architecture Search with Random LabelsCode1
Evolutionary Neural Architecture Search Supporting Approximate Multipliers—0
Self-supervised Cross-silo Federated Neural Architecture Search—0
Towards Improving the Consistency, Efficiency, and Flexibility of Differentiable Neural Architecture Search—0
Investigating Bi-Level Optimization for Learning and Vision from a Unified Perspective: A Survey and Beyond—0
Evolutionary Multi-objective Architecture Search Framework: Application to COVID-19 3D CT ClassificationCode0
A Comprehensive Survey on Hardware-Aware Neural Architecture Search—0
CM-NAS: Cross-Modality Neural Architecture Search for Visible-Infrared Person Re-IdentificationCode1
Zero-Cost Proxies for Lightweight NASCode1
GIID-Net: Generalizable Image Inpainting Detection via Neural Architecture Search and AttentionCode1
Learning Efficient, Explainable and Discriminative Representations for Pulmonary Nodules ClassificationCode1
ES-ENAS: Efficient Evolutionary Optimization for Large Hybrid Search SpacesCode0
Trilevel Neural Architecture Search for Efficient Single Image Super-Resolution—0
Automated Model Design and Benchmarking of 3D Deep Learning Models for COVID-19 Detection with Chest CT ScansCode1
3D-ANAS: 3D Asymmetric Neural Architecture Search for Fast Hyperspectral Image ClassificationCode0
PEng4NN: An Accurate Performance Estimation Engine for Efficient Automated Neural Network Architecture Search—0
DICE: Deep Significance Clustering for Outcome-Aware Stratification—0
Generalized Latency Performance Estimation for Once-For-All Neural Architecture SearchCode0
Topology-aware Tensor Decomposition for Meta-graph Learning—0
Pyramid Architecture Search for Real-Time Image Deblurring—0
iNAS: Integral NAS for Device-Aware Salient Object Detection—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