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 251–275 of 1915 papers

Title	Date	Tasks	Status	Hype	Score
β-DARTS: Beta-Decay Regularization for Differentiable Architecture Search	Mar 3, 2022	Neural Architecture Search	CodeCode Available	1	5
Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective	Feb 23, 2021	GPUNeural Architecture Search	CodeCode Available	1	5
AutoSNN: Towards Energy-Efficient Spiking Neural Networks	Jan 30, 2022	Neural Architecture Search	CodeCode Available	1	5
Neural Architecture Search via Bregman Iterations	Jun 4, 2021	DeblurringDenoising	CodeCode Available	1	5
emoDARTS: Joint Optimisation of CNN & Sequential Neural Network Architectures for Superior Speech Emotion Recognition	Mar 21, 2024	Emotion RecognitionNeural Architecture Search	CodeCode Available	1	5
Efficient Neural Architecture Search via Parameter Sharing	Feb 9, 2018	GPULanguage Modelling	CodeCode Available	1	5
Efficient Neural Architecture Search for End-to-end Speech Recognition via Straight-Through Gradients	Nov 11, 2020	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	CodeCode Available	1	5
EfficientPose: Efficient Human Pose Estimation with Neural Architecture Search	Dec 13, 2020	image-classificationImage Classification	CodeCode Available	1	5
Efficient Hyperparameter Optimization with Adaptive Fidelity Identification	Jan 1, 2024	Bayesian OptimizationHyperparameter Optimization	CodeCode Available	1	5
EfficientTDNN: Efficient Architecture Search for Speaker Recognition	Mar 25, 2021	Data AugmentationNetwork Pruning	CodeCode Available	1	5
BM-NAS: Bilevel Multimodal Neural Architecture Search	Apr 19, 2021	Neural Architecture Search	CodeCode Available	1	5
BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search	Oct 25, 2019	Bayesian OptimizationHyperparameter Optimization	CodeCode Available	1	5
Dataset Condensation with Gradient Matching	Jun 10, 2020	Continual LearningDataset Condensation	CodeCode Available	1	5
Bayesian Model Selection, the Marginal Likelihood, and Generalization	Feb 23, 2022	modelModel Selection	CodeCode Available	1	5
einspace: Searching for Neural Architectures from Fundamental Operations	May 31, 2024	Neural Architecture Search	CodeCode Available	1	5
ElasticViT: Conflict-aware Supernet Training for Deploying Fast Vision Transformer on Diverse Mobile Devices	Mar 17, 2023	Neural Architecture Search	CodeCode Available	1	5
AdvRush: Searching for Adversarially Robust Neural Architectures	Aug 3, 2021	Adversarial RobustnessNeural Architecture Search	CodeCode Available	1	5
EC-NAS: Energy Consumption Aware Tabular Benchmarks for Neural Architecture Search	Oct 12, 2022	Neural Architecture Search	CodeCode Available	1	5
Bayesian Neural Architecture Search using A Training-Free Performance Metric	Jan 29, 2020	Bayesian OptimizationNeural Architecture Search	CodeCode Available	1	5
Bag of Baselines for Multi-objective Joint Neural Architecture Search and Hyperparameter Optimization	May 3, 2021	AutoMLHyperparameter Optimization	CodeCode Available	1	5
β-DARTS++: Bi-level Regularization for Proxy-robust Differentiable Architecture Search	Jan 16, 2023	Neural Architecture Search	CodeCode Available	1	5
BigNAS: Scaling Up Neural Architecture Search with Big Single-Stage Models	Mar 24, 2020	Neural Architecture Search	CodeCode Available	1	5
Evolutionary Neural Cascade Search across Supernetworks	Mar 8, 2022	Neural Architecture Search	CodeCode Available	1	5
Evolving Search Space for Neural Architecture Search	Nov 22, 2020	Knowledge DistillationNeural Architecture Search	CodeCode Available	1	5
Adversarial Branch Architecture Search for Unsupervised Domain Adaptation	Feb 12, 2021	Domain AdaptationModel Selection	CodeCode Available	1	5

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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