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 1251–1275 of 1915 papers

Title	Date	Tasks	Status	Hype
EfficientPose: Efficient Human Pose Estimation with Neural Architecture Search	Dec 13, 2020	image-classificationImage Classification	CodeCode Available	1
Efficient Incorporation of Multiple Latency Targets in the Once-For-All Network	Dec 12, 2020	AllNetwork Pruning	CodeCode Available	0
Differential Evolution for Neural Architecture Search	Dec 11, 2020	Bayesian OptimizationNeural Architecture Search	CodeCode Available	1
AdvantageNAS: Efficient Neural Architecture Search with Credit Assignment	Dec 11, 2020	Neural Architecture Search	CodeCode Available	0
Auto-MVCNN: Neural Architecture Search for Multi-view 3D Shape Recognition	Dec 10, 2020	3D Shape RecognitionNeural Architecture Search	—Unverified	0
Skillearn: Machine Learning Inspired by Humans' Learning Skills	Dec 9, 2020	BIG-bench Machine LearningNeural Architecture Search	—Unverified	0
DiffPrune: Neural Network Pruning with Deterministic Approximate Binary Gates and L_0 Regularization	Dec 7, 2020	Image ClassificationModel Selection	CodeCode Available	0
Batch Group Normalization	Dec 4, 2020	Domain AdaptationFew-Shot Learning	—Unverified	0
Automatic Routability Predictor Development Using Neural Architecture Search	Dec 3, 2020	BIG-bench Machine LearningNeural Architecture Search	—Unverified	0
Wisdom of Committees: An Overlooked Approach To Faster and More Accurate Models	Dec 3, 2020	General Classificationimage-classification	—Unverified	0
CLEARER: Multi-Scale Neural Architecture Search for Image Restoration	Dec 1, 2020	DenoisingGPU	CodeCode Available	1
Understanding and Exploring the Network with Stochastic Architectures	Dec 1, 2020	Neural Architecture Search	CodeCode Available	0
Differentiable Neural Architecture Search in Equivalent Space with Exploration Enhancement	Dec 1, 2020	Bilevel OptimizationNeural Architecture Search	CodeCode Available	0
Revisiting Parameter Sharing for Automatic Neural Channel Number Search	Dec 1, 2020	Neural Architecture Search	CodeCode Available	1
Adapting Neural Architectures Between Domains	Dec 1, 2020	Domain AdaptationGeneralization Bounds	CodeCode Available	0
Optimizing the Neural Architecture of Reinforcement Learning Agents	Nov 30, 2020	Atari GamesMeta Reinforcement Learning	CodeCode Available	0
ScaleNAS: One-Shot Learning of Scale-Aware Representations for Visual Recognition	Nov 30, 2020	Multi-Person Pose EstimationNeural Architecture Search	—Unverified	0
Inter-layer Transition in Neural Architecture Search	Nov 30, 2020	Neural Architecture Search	CodeCode Available	0
Learning by Passing Tests, with Application to Neural Architecture Search	Nov 30, 2020	Neural Architecture Search	—Unverified	0
Multi-objective Neural Architecture Search with Almost No Training	Nov 27, 2020	GPUNeural Architecture Search	—Unverified	0
aw_nas: A Modularized and Extensible NAS framework	Nov 25, 2020	Adversarial RobustnessNeural Architecture Search	—Unverified	0
Bringing AI To Edge: From Deep Learning's Perspective	Nov 25, 2020	Deep LearningEdge-computing	—Unverified	0
A Review of Recent Advances of Binary Neural Networks for Edge Computing	Nov 24, 2020	Edge-computingNeural Architecture Search	—Unverified	0
Efficient Sampling for Predictor-Based Neural Architecture Search	Nov 24, 2020	Neural Architecture Search	—Unverified	0
ROME: Robustifying Memory-Efficient NAS via Topology Disentanglement and Gradient Accumulation	Nov 23, 2020	DisentanglementNeural 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