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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 1126–1150 of 1915 papers

Title	Date	Tasks	Status	Hype
Learning Versatile Neural Architectures by Propagating Network Codes	Mar 24, 2021	Image SegmentationNeural Architecture Search	CodeCode Available	1
Fisher Task Distance and Its Application in Neural Architecture Search	Mar 23, 2021	Neural Architecture SearchTransfer Learning	CodeCode Available	0
BossNAS: Exploring Hybrid CNN-transformers with Block-wisely Self-supervised Neural Architecture Search	Mar 23, 2021	Image ClassificationNeural Architecture Search	CodeCode Available	1
Enhanced Gradient for Differentiable Architecture Search	Mar 23, 2021	ClassificationGeneral Classification	—Unverified	0
AutoSpace: Neural Architecture Search with Less Human Interference	Mar 22, 2021	Neural Architecture Search	CodeCode Available	0
Prioritized Architecture Sampling with Monto-Carlo Tree Search	Mar 22, 2021	Neural Architecture Search	CodeCode Available	1
MoViNets: Mobile Video Networks for Efficient Video Recognition	Mar 21, 2021	Action ClassificationAction Recognition	CodeCode Available	1
HW-NAS-Bench:Hardware-Aware Neural Architecture Search Benchmark	Mar 19, 2021	Hardware Aware Neural Architecture SearchNeural Architecture Search	CodeCode Available	1
GPNAS: A Neural Network Architecture Search Framework Based on Graphical Predictor	Mar 19, 2021	Neural Architecture Search	—Unverified	0
NAS-TC: Neural Architecture Search on Temporal Convolutions for Complex Action Recognition	Mar 17, 2021	Action RecognitionAction Recognition In Videos	—Unverified	0
The Untapped Potential of Off-the-Shelf Convolutional Neural Networks	Mar 17, 2021	Neural Architecture Search	—Unverified	0
Pretraining Neural Architecture Search Controllers with Locality-based Self-Supervised Learning	Mar 15, 2021	Metric LearningNeural Architecture Search	CodeCode Available	0
Neural Architecture Search based on Cartesian Genetic Programming Coding Method	Mar 12, 2021	AutoMLBIG-bench Machine Learning	—Unverified	0
Interleaving Learning, with Application to Neural Architecture Search	Mar 12, 2021	BIG-bench Machine Learningimage-classification	—Unverified	0
Learning by Teaching, with Application to Neural Architecture Search	Mar 11, 2021	Neural Architecture Search	—Unverified	0
HSCoNAS: Hardware-Software Co-Design of Efficient DNNs via Neural Architecture Search	Mar 11, 2021	CPUGPU	—Unverified	0
Trainless Model Performance Estimation for Neural Architecture Search	Mar 10, 2021	modelNeural Architecture Search	—Unverified	0
Contrastive Neural Architecture Search with Neural Architecture Comparators	Mar 8, 2021	Neural Architecture Search	CodeCode Available	1
OPANAS: One-Shot Path Aggregation Network Architecture Search for Object Detection	Mar 8, 2021	GPUNeural Architecture Search	CodeCode Available	1
Efficient Model Performance Estimation via Feature Histories	Mar 7, 2021	image-classificationImage Classification	—Unverified	0
Auto-tuning of Deep Neural Networks by Conflicting Layer Removal	Mar 7, 2021	Neural Architecture Search	CodeCode Available	0
Deep reinforcement learning in medical imaging: A literature review	Mar 5, 2021	Deep Reinforcement LearningLesion Detection	—Unverified	0
Differentiable Neural Architecture Learning for Efficient Neural Network Design	Mar 3, 2021	Efficient Neural NetworkNeural Architecture Search	CodeCode Available	1
Improving Neural Networks for Time Series Forecasting using Data Augmentation and AutoML	Mar 2, 2021	AutoMLBIG-bench Machine Learning	CodeCode Available	0
Task-Adaptive Neural Network Search with Meta-Contrastive Learning	Mar 2, 2021	AutoMLContrastive Learning	CodeCode Available	1

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All datasets ImageNet NAS-Bench-201, ImageNet-16-120 CIFAR-10 NAS-Bench-201, CIFAR-100 NAS-Bench-201, CIFAR-10 CIFAR-10 Image Classification CIFAR-100 NATS-Bench Topology, CIFAR-10 NATS-Bench Topology, CIFAR-100 NATS-Bench Topology, ImageNet16-120 Food-101 NAS-Bench-101

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	SPOS (ProxylessNAS (GPU) latency)	Accuracy	75.3	—	Unverified
2	SPOS (FBNet-C latency)	Accuracy	75.1	—	Unverified
3	SPOS (block search + channel search)	Accuracy	74.7	—	Unverified
4	MUXNet-xs	Top-1 Error Rate	33.3	—	Unverified
5	FBNetV2-F1	Top-1 Error Rate	31.7	—	Unverified
6	LayerNAS-60M	Top-1 Error Rate	31	—	Unverified
7	NASGEP	Top-1 Error Rate	29.51	—	Unverified
8	MUXNet-s	Top-1 Error Rate	28.4	—	Unverified
9	NN-MASS-A	Top-1 Error Rate	27.1	—	Unverified
10	FBNetV2-F3	Top-1 Error Rate	26.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CR-LSO	Accuracy (Test)	46.98	—	Unverified
2	Shapley-NAS	Accuracy (Test)	46.85	—	Unverified
3	β-RDARTS-L2	Accuracy (Test)	46.71	—	Unverified
4	β-SDARTS-RS	Accuracy (Test)	46.71	—	Unverified
5	ASE-NAS+	Accuracy (Val)	46.66	—	Unverified
6	NAR	Accuracy (Test)	46.66	—	Unverified
7	BaLeNAS-TF	Accuracy (Test)	46.54	—	Unverified
8	AG-Net	Accuracy (Test)	46.42	—	Unverified
9	Local search	Accuracy (Test)	46.38	—	Unverified
10	NASBOT	Accuracy (Test)	46.37	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Balanced Mixture	Accuracy (% )	91.55	—	Unverified
2	GDAS	Top-1 Error Rate	3.4	—	Unverified
3	Bonsai-Net	Top-1 Error Rate	3.35	—	Unverified
4	Net2 (2)	Top-1 Error Rate	3.3	—	Unverified
5	μDARTS	Top-1 Error Rate	3.28	—	Unverified
6	NN-MASS- CIFAR-C	Top-1 Error Rate	3.18	—	Unverified
7	NN-MASS- CIFAR-A	Top-1 Error Rate	3	—	Unverified
8	DARTS (first order)	Top-1 Error Rate	3	—	Unverified
9	NASGEP	Top-1 Error Rate	2.82	—	Unverified
10	AlphaX-1 (cutout NASNet)	Top-1 Error Rate	2.82	—	Unverified