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 1051–1075 of 1915 papers

Title	Date	Tasks	Status	Hype
Zero-Cost Operation Scoring in Differentiable Architecture Search	Jun 12, 2021	GPUNeural Architecture Search	CodeCode Available	0
HR-NAS: Searching Efficient High-Resolution Neural Architectures with Lightweight Transformers	Jun 11, 2021	image-classificationImage Classification	CodeCode Available	1
Accelerating Neural Architecture Search via Proxy Data	Jun 9, 2021	GPUNeural Architecture Search	CodeCode Available	1
Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing	Jun 8, 2021	Federated LearningHyperparameter Optimization	—Unverified	0
MONCAE: Multi-Objective Neuroevolution of Convolutional Autoencoders	Jun 7, 2021	AutoMLimage-classification	—Unverified	0
FEAR: A Simple Lightweight Method to Rank Architectures	Jun 7, 2021	Neural Architecture Search	CodeCode Available	1
Encoder-Decoder Neural Architecture Optimization for Keyword Spotting	Jun 4, 2021	DecoderKeyword Spotting	—Unverified	0
Event Classification with Multi-step Machine Learning	Jun 4, 2021	BIG-bench Machine LearningClassification	CodeCode Available	0
Neural Architecture Search via Bregman Iterations	Jun 4, 2021	DeblurringDenoising	CodeCode Available	1
Differentiable Architecture Search for Reinforcement Learning	Jun 4, 2021	Neural Architecture Searchreinforcement-learning	CodeCode Available	1
A Survey on Optimal Transport for Machine Learning: Theory and Applications	Jun 3, 2021	BIG-bench Machine LearningDomain Adaptation	—Unverified	0
Discovering Better Model Architectures for Medical Query Understanding	Jun 1, 2021	modelNatural Language Inference	—Unverified	0
Relational Graph Neural Network Design via Progressive Neural Architecture Search	May 30, 2021	Graph Neural NetworkNeural Architecture Search	—Unverified	0
Evolution of Activation Functions: An Empirical Investigation	May 30, 2021	Neural Architecture Search	—Unverified	0
NAS-BERT: Task-Agnostic and Adaptive-Size BERT Compression with Neural Architecture Search	May 30, 2021	Language ModellingModel Compression	—Unverified	0
FuSeConv: Fully Separable Convolutions for Fast Inference on Systolic Arrays	May 27, 2021	Neural Architecture Search	CodeCode Available	1
Joint-DetNAS: Upgrade Your Detector with NAS, Pruning and Dynamic Distillation	May 27, 2021	Knowledge DistillationNeural Architecture Search	—Unverified	0
The Nonlinearity Coefficient -- A Practical Guide to Neural Architecture Design	May 25, 2021	Neural Architecture Search	—Unverified	0
AutoReCon: Neural Architecture Search-based Reconstruction for Data-free Compression	May 25, 2021	Neural Architecture Search	CodeCode Available	1
FNAS: Uncertainty-Aware Fast Neural Architecture Search	May 25, 2021	FairnessGPU	—Unverified	0
TransNAS-Bench-101: Improving Transferability and Generalizability of Cross-Task Neural Architecture Search	May 25, 2021	Neural Architecture SearchTransfer Learning	CodeCode Available	1
Searching Collaborative Agents for Multi-plane Localization in 3D Ultrasound	May 22, 2021	DiagnosticMulti-agent Reinforcement Learning	—Unverified	0
A General Method For Automatic Discovery of Powerful Interactions In Click-Through Rate Prediction	May 21, 2021	Click-Through Rate PredictionNeural Architecture Search	—Unverified	0
ViPNAS: Efficient Video Pose Estimation via Neural Architecture Search	May 21, 2021	CPUNeural Architecture Search	CodeCode Available	1
Ranking Architectures by Feature Extraction Capabilities	May 20, 2021	Neural Architecture Search	—Unverified	0

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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