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 526–550 of 1915 papers

Title	Date	Tasks	Status	Hype
SuperFedNAS: Cost-Efficient Federated Neural Architecture Search for On-Device Inference	Jan 26, 2023	Federated LearningNeural Architecture Search	—Unverified	0
ZiCo: Zero-shot NAS via Inverse Coefficient of Variation on Gradients	Jan 26, 2023	GPUimage-classification	CodeCode Available	1
Lightweight Neural Architecture Search for Temporal Convolutional Networks at the Edge	Jan 24, 2023	GPUimage-classification	CodeCode Available	1
RD-NAS: Enhancing One-shot Supernet Ranking Ability via Ranking Distillation from Zero-cost Proxies	Jan 24, 2023	Computational EfficiencyNeural Architecture Search	CodeCode Available	1
GP-NAS-ensemble: a model for NAS Performance Prediction	Jan 23, 2023	Ensemble LearningNeural Architecture Search	—Unverified	0
Enabling Hard Constraints in Differentiable Neural Network and Accelerator Co-Exploration	Jan 23, 2023	Neural Architecture Search	—Unverified	0
Efficient Training Under Limited Resources	Jan 23, 2023	Data AugmentationNeural Architecture Search	CodeCode Available	0
Neural Architecture Search: Insights from 1000 Papers	Jan 20, 2023	Natural Language UnderstandingNeural Architecture Search	CodeCode Available	0
RNAS-CL: Robust Neural Architecture Search by Cross-Layer Knowledge Distillation	Jan 19, 2023	Knowledge DistillationNeural Architecture Search	—Unverified	0
Accurate Detection of Paroxysmal Atrial Fibrillation with Certified-GAN and Neural Architecture Search	Jan 17, 2023	Generative Adversarial NetworkNeural Architecture Search	—Unverified	0
DQNAS: Neural Architecture Search using Reinforcement Learning	Jan 17, 2023	Face RecognitionNeural Architecture Search	—Unverified	0
β-DARTS++: Bi-level Regularization for Proxy-robust Differentiable Architecture Search	Jan 16, 2023	Neural Architecture Search	CodeCode Available	1
Efficient Evaluation Methods for Neural Architecture Search: A Survey	Jan 14, 2023	Neural Architecture SearchSurvey	—Unverified	0
Adaptive Neural Networks Using Residual Fitting	Jan 13, 2023	Imitation LearningNeural Architecture Search	—Unverified	0
Pruning Compact ConvNets for Efficient Inference	Jan 11, 2023	GPUNetwork Pruning	—Unverified	0
On Finding Small Hyper-Gradients in Bilevel Optimization: Hardness Results and Improved Analysis	Jan 2, 2023	Bilevel OptimizationMeta-Learning	—Unverified	0
Extensible and Efficient Proxy for Neural Architecture Search	Jan 1, 2023	GPUNeural Architecture Search	—Unverified	0
TripLe: Revisiting Pretrained Model Reuse and Progressive Learning for Efficient Vision Transformer Scaling and Searching	Jan 1, 2023	Knowledge DistillationNeural Architecture Search	—Unverified	0
Continual Segment: Towards a Single, Unified and Non-forgetting Continual Segmentation Model of 143 Whole-body Organs in CT Scans	Jan 1, 2023	Continual Semantic SegmentationDecoder	—Unverified	0
Unleashing the Power of Gradient Signal-to-Noise Ratio for Zero-Shot NAS	Jan 1, 2023	Neural Architecture Search	CodeCode Available	0
HOTNAS: Hierarchical Optimal Transport for Neural Architecture Search	Jan 1, 2023	Bayesian OptimizationNeural Architecture Search	—Unverified	0
EMT-NAS:Transferring Architectural Knowledge Between Tasks From Different Datasets	Jan 1, 2023	Multi-Task LearningNeural Architecture Search	CodeCode Available	0
Pseudo-Inverted Bottleneck Convolution for DARTS Search Space	Dec 31, 2022	Neural Architecture Search	CodeCode Available	0
Breaking the Architecture Barrier: A Method for Efficient Knowledge Transfer Across Networks	Dec 28, 2022	Neural Architecture SearchParameter Prediction	—Unverified	0
DAS: Neural Architecture Search via Distinguishing Activation Score	Dec 23, 2022	Neural Architecture Search	—Unverified	0

Show:10 25 50

← PrevPage 22 of 77Next →

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-SDARTS-RS	Accuracy (Test)	46.71	—	Unverified
4	β-RDARTS-L2	Accuracy (Test)	46.71	—	Unverified
5	NAR	Accuracy (Test)	46.66	—	Unverified
6	ASE-NAS+	Accuracy (Val)	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	DARTS (first order)	Top-1 Error Rate	3	—	Unverified
8	NN-MASS- CIFAR-A	Top-1 Error Rate	3	—	Unverified
9	AlphaX-1 (cutout NASNet)	Top-1 Error Rate	2.82	—	Unverified
10	NASGEP	Top-1 Error Rate	2.82	—	Unverified