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 1676–1700 of 1915 papers

Title	Date	Tasks	Status
Fair DARTS: Eliminating Unfair Advantages in Differentiable Architecture Search	Nov 27, 2019	AutoMLNeural Architecture Search	CodeCode Available
Boosting Order-Preserving and Transferability for Neural Architecture Search: a Joint Architecture Refined Search and Fine-tuning Approach	Mar 18, 2024	Neural Architecture Search	CodeCode Available
ShiftNAS: Improving One-shot NAS via Probability Shift	Jul 17, 2023	AttributeNeural Architecture Search	CodeCode Available
MFAS: Multimodal Fusion Architecture Search	Jun 1, 2019	Action RecognitionGeneral Classification	CodeCode Available
Bonsai-Net: One-Shot Neural Architecture Search via Differentiable Pruners	Jun 12, 2020	Neural Architecture Search	CodeCode Available
Adaptive Search-and-Training for Robust and Efficient Network Pruning	Feb 1, 2023	Knowledge DistillationNetwork Pruning	CodeCode Available
BOAH: A Tool Suite for Multi-Fidelity Bayesian Optimization & Analysis of Hyperparameters	Aug 16, 2019	Bayesian OptimizationHyperparameter Optimization	CodeCode Available
Shortest Edit Path Crossover: A Theory-driven Solution to the Permutation Problem in Evolutionary Neural Architecture Search	Oct 25, 2022	Evolutionary AlgorithmsNeural Architecture Search	CodeCode Available
BLOX: Macro Neural Architecture Search Benchmark and Algorithms	Oct 13, 2022	Neural Architecture Search	CodeCode Available
Exploring Unexplored Tensor Network Decompositions for Convolutional Neural Networks	Dec 1, 2019	Model CompressionNeural Architecture Search	CodeCode Available
Exploring Robust Architectures for Deep Artificial Neural Networks	Jun 30, 2021	AutoMLimage-classification	CodeCode Available
Exploring Randomly Wired Neural Networks for Image Recognition	Apr 2, 2019	Image ClassificationNeural Architecture Search	CodeCode Available
Tree ensemble kernels for Bayesian optimization with known constraints over mixed-feature spaces	Jul 2, 2022	Bayesian OptimizationNeural Architecture Search	CodeCode Available
Blending Diverse Physical Priors with Neural Networks	Oct 1, 2019	Neural Architecture Search	CodeCode Available
Ps and Qs: Quantization-aware pruning for efficient low latency neural network inference	Feb 22, 2021	Bayesian OptimizationComputational Efficiency	CodeCode Available
Shrink-Perturb Improves Architecture Mixing during Population Based Training for Neural Architecture Search	Jul 28, 2023	Hyperparameter OptimizationImage Generation	CodeCode Available
Experiments on Properties of Hidden Structures of Sparse Neural Networks	Jul 27, 2021	Neural Architecture SearchPrediction	CodeCode Available
Mixture-of-Supernets: Improving Weight-Sharing Supernet Training with Architecture-Routed Mixture-of-Experts	Jun 8, 2023	Language ModelingLanguage Modelling	CodeCode Available
Evolving Robust Neural Architectures to Defend from Adversarial Attacks	Jun 27, 2019	Neural Architecture Search	CodeCode Available
Evolving Neural Networks through Augmenting Topologies	Mar 13, 2006	Neural Architecture SearchReinforcement Learning	CodeCode Available
MobileDets: Searching for Object Detection Architectures for Mobile Accelerators	Apr 30, 2020	CPUGPU	CodeCode Available
Evolving Neural Architecture Using One Shot Model	Dec 23, 2020	GPUmodel	CodeCode Available
Pseudo-Inverted Bottleneck Convolution for DARTS Search Space	Dec 31, 2022	Neural Architecture Search	CodeCode Available
Evolutionary NAS with Gene Expression Programming of Cellular Encoding	May 27, 2020	General ClassificationGPU	CodeCode Available
TreeGrad: Transferring Tree Ensembles to Neural Networks	Apr 25, 2019	BIG-bench Machine LearningNeural Architecture Search	CodeCode Available

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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