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 1026–1050 of 1915 papers

Title	Date	Tasks	Status	Hype
Integrating Large Circular Kernels into CNNs through Neural Architecture Search	Jul 6, 2021	Data AugmentationNeural Architecture Search	CodeCode Available	1
Mutation is all you need	Jul 4, 2021	AllBayesian Optimization	—Unverified	0
CHASE: Robust Visual Tracking via Cell-Level Differentiable Neural Architecture Search	Jul 2, 2021	Neural Architecture SearchSemantic Segmentation	CodeCode Available	0
Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets	Jul 2, 2021	GPUMeta-Learning	CodeCode Available	1
Exploring Robust Architectures for Deep Artificial Neural Networks	Jun 30, 2021	AutoMLimage-classification	CodeCode Available	0
Poisoning the Search Space in Neural Architecture Search	Jun 28, 2021	Autonomous DrivingImage Segmentation	—Unverified	0
BiX-NAS: Searching Efficient Bi-directional Architecture for Medical Image Segmentation	Jun 26, 2021	Image SegmentationMedical Image Segmentation	CodeCode Available	1
ViTAS: Vision Transformer Architecture Search	Jun 25, 2021	Inductive BiasNeural Architecture Search	CodeCode Available	1
AutoAdapt: Automated Segmentation Network Search for Unsupervised Domain Adaptation	Jun 24, 2021	Domain AdaptationNeural Architecture Search	—Unverified	0
Bayesian Deep Learning Hyperparameter Search for Robust Function Mapping to Polynomials with Noise	Jun 23, 2021	Neural Architecture SearchUncertainty Quantification	—Unverified	0
Multi-objective Asynchronous Successive Halving	Jun 23, 2021	FairnessHyperparameter Optimization	CodeCode Available	3
NAX: Co-Designing Neural Network and Hardware Architecture for Memristive Xbar based Computing Systems	Jun 23, 2021	Neural Architecture Search	—Unverified	0
DARTS-PRIME: Regularization and Scheduling Improve Constrained Optimization in Differentiable NAS	Jun 22, 2021	Bilevel OptimizationNeural Architecture Search	—Unverified	0
Connection Sensitivity Matters for Training-free DARTS: From Architecture-Level Scoring to Operation-Level Sensitivity Analysis	Jun 22, 2021	Computational EfficiencyNetwork Pruning	—Unverified	0
Latency-Aware Neural Architecture Search with Multi-Objective Bayesian Optimization	Jun 22, 2021	Bayesian OptimizationNatural Language Understanding	—Unverified	0
iDARTS: Differentiable Architecture Search with Stochastic Implicit Gradients	Jun 21, 2021	Neural Architecture Search	CodeCode Available	1
Removing Raindrops and Rain Streaks in One Go	Jun 19, 2021	Neural Architecture SearchRaindrop Removal	CodeCode Available	1
ReNAS: Relativistic Evaluation of Neural Architecture Search	Jun 19, 2021	Neural Architecture Search	CodeCode Available	0
RHNAS: Realizable Hardware and Neural Architecture Search	Jun 17, 2021	Neural Architecture Search	—Unverified	0
How does topology of neural architectures impact gradient propagation and model performance?	Jun 16, 2021	Model CompressionNeural Architecture Search	CodeCode Available	0
HELP: Hardware-Adaptive Efficient Latency Prediction for NAS via Meta-Learning	Jun 16, 2021	Meta-LearningNeural Architecture Search	CodeCode Available	1
Redefining Neural Architecture Search of Heterogeneous Multi-Network Models by Characterizing Variation Operators and Model Components	Jun 16, 2021	Neural Architecture Search	—Unverified	0
Learning Deep Morphological Networks with Neural Architecture Search	Jun 14, 2021	Edge DetectionMeta-Learning	CodeCode Available	0
Differentiable Neural Architecture Search with Morphism-based Transformable Backbone Architectures	Jun 14, 2021	Language ModelingLanguage Modelling	—Unverified	0
LENAS: Learning-based Neural Architecture Search and Ensemble for 3D Radiotherapy Dose Prediction	Jun 12, 2021	DiversityEnsemble Learning	CodeCode Available	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