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

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Showing 901–925 of 1915 papers

Title	Date	Tasks	Status
NAS-PRNet: Neural Architecture Search generated Phase Retrieval Net for Off-axis Quantitative Phase Imaging	Oct 25, 2022	DecoderNeural Architecture Search	—Unverified
NASA: Neural Architecture Search and Acceleration for Hardware Inspired Hybrid Networks	Oct 24, 2022	Neural Architecture Search	CodeCode Available
BASQ: Branch-wise Activation-clipping Search Quantization for Sub-4-bit Neural Networks	Oct 23, 2022	Neural Architecture SearchQuantization	CodeCode Available
Neural Architectural Backdoors	Oct 21, 2022	AutoMLNeural Architecture Search	—Unverified
OpenEarthMap: A Benchmark Dataset for Global High-Resolution Land Cover Mapping	Oct 19, 2022	Domain AdaptationNeural Architecture Search	—Unverified
Multi-Agent Automated Machine Learning	Oct 17, 2022	AutoMLData Augmentation	—Unverified
HQNAS: Auto CNN deployment framework for joint quantization and architecture search	Oct 16, 2022	GPUNeural Architecture Search	—Unverified
FAQS: Communication-efficient Federate DNN Architecture and Quantization Co-Search for personalized Hardware-aware Preferences	Oct 16, 2022	Neural Architecture SearchQuantization	—Unverified
Λ-DARTS: Mitigating Performance Collapse by Harmonizing Operation Selection among Cells	Oct 14, 2022	Neural Architecture Search	CodeCode Available
BLOX: Macro Neural Architecture Search Benchmark and Algorithms	Oct 13, 2022	Neural Architecture Search	CodeCode Available
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
Analyzing the Expected Hitting Time of Evolutionary Computation-based Neural Architecture Search Algorithms	Oct 11, 2022	Neural Architecture Search	—Unverified
Equivariance-aware Architectural Optimization of Neural Networks	Oct 11, 2022	Neural Architecture Search	—Unverified
LidarNAS: Unifying and Searching Neural Architectures for 3D Point Clouds	Oct 10, 2022	3D Object DetectionAutonomous Driving	—Unverified
Unified Probabilistic Neural Architecture and Weight Ensembling Improves Model Robustness	Oct 8, 2022	Bayesian InferenceNeural Architecture Search	—Unverified
Inference Latency Prediction at the Edge	Oct 6, 2022	DiversityNeural Architecture Search	—Unverified
POPNASv2: An Efficient Multi-Objective Neural Architecture Search Technique	Oct 6, 2022	Neural Architecture Search	—Unverified
NAS-Bench-Suite-Zero: Accelerating Research on Zero Cost Proxies	Oct 6, 2022	AutoMLNeural Architecture Search	—Unverified
Toward Edge-Efficient Dense Predictions with Synergistic Multi-Task Neural Architecture Search	Oct 4, 2022	Hardware Aware Neural Architecture SearchNeural Architecture Search	—Unverified
Energy Consumption of Neural Networks on NVIDIA Edge Boards: an Empirical Model	Oct 4, 2022	Network PruningNeural Architecture Search	—Unverified
DARTFormer: Finding The Best Type Of Attention	Oct 2, 2022	ListOpsNeural Architecture Search	—Unverified
Siamese-NAS: Using Trained Samples Efficiently to Find Lightweight Neural Architecture by Prior Knowledge	Oct 2, 2022	Neural Architecture Search	CodeCode Available
IMB-NAS: Neural Architecture Search for Imbalanced Datasets	Sep 30, 2022	Neural Architecture SearchRepresentation Learning	—Unverified
BayesFT: Bayesian Optimization for Fault Tolerant Neural Network Architecture	Sep 30, 2022	Bayesian Optimizationimage-classification	CodeCode Available
Automated Mobile Attention KPConv Networks via a Wide and Deep Predictor	Sep 28, 2022	3D Point Cloud ClassificationFeature Engineering	—Unverified

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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-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