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 601–625 of 1915 papers

Title	Date	Tasks	Status	Hype
EC-NAS: Energy Consumption Aware Tabular Benchmarks for Neural Architecture Search	Oct 12, 2022	Neural Architecture Search	CodeCode Available	1
Analyzing the Expected Hitting Time of Evolutionary Computation-based Neural Architecture Search Algorithms	Oct 11, 2022	Neural Architecture Search	—Unverified	0
RoHNAS: A Neural Architecture Search Framework with Conjoint Optimization for Adversarial Robustness and Hardware Efficiency of Convolutional and Capsule Networks	Oct 11, 2022	Adversarial RobustnessGPU	CodeCode Available	0
Equivariance-aware Architectural Optimization of Neural Networks	Oct 11, 2022	Neural Architecture Search	—Unverified	0
LidarNAS: Unifying and Searching Neural Architectures for 3D Point Clouds	Oct 10, 2022	3D Object DetectionAutonomous Driving	—Unverified	0
Unified Probabilistic Neural Architecture and Weight Ensembling Improves Model Robustness	Oct 8, 2022	Bayesian InferenceNeural Architecture Search	—Unverified	0
Demystifying Map Space Exploration for NPUs	Oct 7, 2022	NavigateNeural Architecture Search	CodeCode Available	1
NAS-Bench-Suite-Zero: Accelerating Research on Zero Cost Proxies	Oct 6, 2022	AutoMLNeural Architecture Search	—Unverified	0
Inference Latency Prediction at the Edge	Oct 6, 2022	DiversityNeural Architecture Search	—Unverified	0
POPNASv2: An Efficient Multi-Objective Neural Architecture Search Technique	Oct 6, 2022	Neural Architecture Search	—Unverified	0
Toward Edge-Efficient Dense Predictions with Synergistic Multi-Task Neural Architecture Search	Oct 4, 2022	Hardware Aware Neural Architecture SearchNeural Architecture Search	—Unverified	0
Energy Consumption of Neural Networks on NVIDIA Edge Boards: an Empirical Model	Oct 4, 2022	Network PruningNeural Architecture Search	—Unverified	0
DARTFormer: Finding The Best Type Of Attention	Oct 2, 2022	ListOpsNeural Architecture Search	—Unverified	0
Siamese-NAS: Using Trained Samples Efficiently to Find Lightweight Neural Architecture by Prior Knowledge	Oct 2, 2022	Neural Architecture Search	CodeCode Available	0
Cross Task Neural Architecture Search for EEG Signal Classifications	Oct 1, 2022	Brain Computer InterfaceEEG	CodeCode Available	1
BayesFT: Bayesian Optimization for Fault Tolerant Neural Network Architecture	Sep 30, 2022	Bayesian Optimizationimage-classification	CodeCode Available	0
IMB-NAS: Neural Architecture Search for Imbalanced Datasets	Sep 30, 2022	Neural Architecture SearchRepresentation Learning	—Unverified	0
Hyper-Representations as Generative Models: Sampling Unseen Neural Network Weights	Sep 29, 2022	Knowledge DistillationNeural Architecture Search	CodeCode Available	1
Automated Mobile Attention KPConv Networks via a Wide and Deep Predictor	Sep 28, 2022	3D Point Cloud ClassificationFeature Engineering	—Unverified	0
Towards Regression-Free Neural Networks for Diverse Compute Platforms	Sep 27, 2022	Neural Architecture Searchregression	—Unverified	0
Hitchhiker's Guide to Super-Resolution: Introduction and Recent Advances	Sep 27, 2022	Neural Architecture SearchSuper-Resolution	—Unverified	0
Searching a High-Performance Feature Extractor for Text Recognition Network	Sep 27, 2022	Neural Architecture SearchVocal Bursts Intensity Prediction	—Unverified	0
SpeedLimit: Neural Architecture Search for Quantized Transformer Models	Sep 25, 2022	Neural Architecture SearchQuantization	—Unverified	0
Tiered Pruning for Efficient Differentialble Inference-Aware Neural Architecture Search	Sep 23, 2022	image-classificationImage Classification	—Unverified	0
NasHD: Efficient ViT Architecture Performance Ranking using Hyperdimensional Computing	Sep 23, 2022	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