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 1276–1300 of 1915 papers

Title	Date	Tasks	Status	Hype
Evolving Search Space for Neural Architecture Search	Nov 22, 2020	Knowledge DistillationNeural Architecture Search	CodeCode Available	1
FP-NAS: Fast Probabilistic Neural Architecture Search	Nov 22, 2020	Neural Architecture Search	—Unverified	0
Continuous Ant-Based Neural Topology Search	Nov 21, 2020	Neural Architecture SearchTime Series	—Unverified	0
BARS: Joint Search of Cell Topology and Layout for Accurate and Efficient Binary ARchitectures	Nov 21, 2020	Neural Architecture Search	—Unverified	0
Large Scale Neural Architecture Search with Polyharmonic Splines	Nov 20, 2020	image-classificationImage Classification	—Unverified	0
Effective, Efficient and Robust Neural Architecture Search	Nov 19, 2020	Adversarial RobustnessNeural Architecture Search	—Unverified	0
Stretchable Cells Help DARTS Search Better	Nov 18, 2020	Neural Architecture Search	—Unverified	0
AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling	Nov 18, 2020	Neural Architecture Search	CodeCode Available	1
EvoPose2D: Pushing the Boundaries of 2D Human Pose Estimation using Accelerated Neuroevolution with Weight Transfer	Nov 17, 2020	2D Human Pose EstimationKeypoint Detection	CodeCode Available	1
Reducing Inference Latency with Concurrent Architectures for Image Recognition	Nov 13, 2020	Neural Architecture Search	—Unverified	0
Towards NNGP-guided Neural Architecture Search	Nov 11, 2020	Neural Architecture Search	CodeCode Available	0
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
Neural Architecture Search with an Efficient Multiobjective Evolutionary Framework	Nov 9, 2020	Cardiac Segmentationimage-classification	—Unverified	0
Adaptive Linear Span Network for Object Skeleton Detection	Nov 8, 2020	Edge DetectionNeural Architecture Search	CodeCode Available	1
FDNAS: Improving Data Privacy and Model Diversity in AutoML	Nov 6, 2020	AutoMLDiversity	—Unverified	0
DAIS: Automatic Channel Pruning via Differentiable Annealing Indicator Search	Nov 4, 2020	Neural Architecture Search	CodeCode Available	0
Channel Planting for Deep Neural Networks using Knowledge Distillation	Nov 4, 2020	Knowledge DistillationNetwork Pruning	—Unverified	0
VEGA: Towards an End-to-End Configurable AutoML Pipeline	Nov 3, 2020	AutoMLBIG-bench Machine Learning	CodeCode Available	1
NAS-FAS: Static-Dynamic Central Difference Network Search for Face Anti-Spoofing	Nov 3, 2020	Face Anti-SpoofingFace Recognition	—Unverified	0
PV-NAS: Practical Neural Architecture Search for Video Recognition	Nov 2, 2020	Neural Architecture SearchVideo Recognition	—Unverified	0
FENAS: Flexible and Expressive Neural Architecture Search	Nov 1, 2020	image-classificationImage Classification	—Unverified	0
Neural Network Design: Learning from Neural Architecture Search	Nov 1, 2020	Benchmarkingimage-classification	CodeCode Available	0
Self-supervised Representation Learning for Evolutionary Neural Architecture Search	Oct 31, 2020	Contrastive LearningGraph Neural Network	CodeCode Available	0
Resource-Aware Pareto-Optimal Automated Machine Learning Platform	Oct 30, 2020	AutoMLBayesian Optimization	—Unverified	0
AgEBO-Tabular: Joint Neural Architecture and Hyperparameter Search with Autotuned Data-Parallel Training for Tabular Data	Oct 30, 2020	AutoMLBayesian Optimization	—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