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 1151–1175 of 1915 papers

Title	Date	Tasks	Status	Hype
A-DeepPixBis: Attentional Angular Margin for Face Anti-Spoofing	Mar 1, 2021	Binary ClassificationFace Anti-Spoofing	—Unverified	0
Automated Machine Learning on Graphs: A Survey	Mar 1, 2021	AutoMLBIG-bench Machine Learning	CodeCode Available	1
Tiny Adversarial Mulit-Objective Oneshot Neural Architecture Search	Feb 28, 2021	Neural Architecture Search	—Unverified	0
Improved Automated Machine Learning from Transfer Learning	Feb 27, 2021	BIG-bench Machine LearningGPU	CodeCode Available	0
Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective	Feb 23, 2021	GPUNeural Architecture Search	CodeCode Available	1
HardCoRe-NAS: Hard Constrained diffeRentiable Neural Architecture Search	Feb 23, 2021	Neural Architecture Search	CodeCode Available	1
Sandwich Batch Normalization: A Drop-In Replacement for Feature Distribution Heterogeneity	Feb 22, 2021	Adversarial DefenseConditional Image Generation	CodeCode Available	1
A Novel Framework for Neural Architecture Search in the Hill Climbing Domain	Feb 22, 2021	GPUNeural Architecture Search	—Unverified	0
Ps and Qs: Quantization-aware pruning for efficient low latency neural network inference	Feb 22, 2021	Bayesian OptimizationComputational Efficiency	CodeCode Available	0
Stronger NAS with Weaker Predictors	Feb 21, 2021	Neural Architecture Search	CodeCode Available	1
Contrastive Self-supervised Neural Architecture Search	Feb 21, 2021	Neural Architecture SearchSelf-Supervised Learning	CodeCode Available	0
BSQ: Exploring Bit-Level Sparsity for Mixed-Precision Neural Network Quantization	Feb 20, 2021	Neural Architecture SearchQuantization	CodeCode Available	1
Towards Accurate and Compact Architectures via Neural Architecture Transformer	Feb 20, 2021	Neural Architecture Searchvalid	CodeCode Available	1
Firefly Neural Architecture Descent: a General Approach for Growing Neural Networks	Feb 17, 2021	Continual Learningimage-classification	CodeCode Available	1
Rethinking Co-design of Neural Architectures and Hardware Accelerators	Feb 17, 2021	Neural Architecture Search	—Unverified	0
AlphaNet: Improved Training of Supernets with Alpha-Divergence	Feb 16, 2021	Image ClassificationNeural Architecture Search	CodeCode Available	1
EPE-NAS: Efficient Performance Estimation Without Training for Neural Architecture Search	Feb 16, 2021	GPUNeural Architecture Search	CodeCode Available	1
Dataset Condensation with Differentiable Siamese Augmentation	Feb 16, 2021	Continual LearningData Augmentation	CodeCode Available	0
Multi-Objective Meta Learning	Feb 14, 2021	Domain AdaptationFew-Shot Learning	—Unverified	0
CATE: Computation-aware Neural Architecture Encoding with Transformers	Feb 14, 2021	AutoMLNeural Architecture Search	CodeCode Available	1
Adversarial Branch Architecture Search for Unsupervised Domain Adaptation	Feb 12, 2021	Domain AdaptationModel Selection	CodeCode Available	1
Neural Architecture Search as Program Transformation Exploration	Feb 12, 2021	Neural Architecture Search	CodeCode Available	1
Regional Attention with Architecture-Rebuilt 3D Network for RGB-D Gesture Recognition	Feb 10, 2021	Gesture RecognitionNeural Architecture Search	CodeCode Available	1
Searching for Fast Model Families on Datacenter Accelerators	Feb 10, 2021	modelNeural Architecture Search	—Unverified	0
Contrastive Embeddings for Neural Architectures	Feb 8, 2021	Contrastive LearningNeural Architecture Search	CodeCode Available	1

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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