SOTAVerified

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

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Showing 51–100 of 1915 papers

TitleStatusHype
Multi-objective Differentiable Neural Architecture SearchCode1
Group Distributionally Robust Dataset Distillation with Risk MinimizationCode1
G-NAS: Generalizable Neural Architecture Search for Single Domain Generalization Object DetectionCode1
Efficient Hyperparameter Optimization with Adaptive Fidelity IdentificationCode1
OTOv3: Automatic Architecture-Agnostic Neural Network Training and Compression from Structured Pruning to Erasing OperatorsCode1
Enhancing Neural Architecture Search with Multiple Hardware Constraints for Deep Learning Model Deployment on Tiny IoT DevicesCode1
Evolutionary Neural Architecture Search for Transformer in Knowledge TracingCode1
DataDAM: Efficient Dataset Distillation with Attention MatchingCode1
Harmonic-NAS: Hardware-Aware Multimodal Neural Architecture Search on Resource-constrained DevicesCode1
AutoML4ETC: Automated Neural Architecture Search for Real-World Encrypted Traffic ClassificationCode1
Uncertainty Quantification for Molecular Property Predictions with Graph Neural Architecture SearchCode1
Designing Novel Cognitive Diagnosis Models via Evolutionary Multi-Objective Neural Architecture SearchCode1
Zero-Shot Neural Architecture Search: Challenges, Solutions, and OpportunitiesCode1
Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed SpacesCode1
Neural Fine-Tuning Search for Few-Shot LearningCode1
Generalizable Lightweight Proxy for Robust NAS against Diverse PerturbationsCode1
ColdNAS: Search to Modulate for User Cold-Start RecommendationCode1
LLMatic: Neural Architecture Search via Large Language Models and Quality Diversity OptimizationCode1
Training-free Neural Architecture Search for RNNs and TransformersCode1
DiffusionNAG: Predictor-guided Neural Architecture Generation with Diffusion ModelsCode1
Meta-prediction Model for Distillation-Aware NAS on Unseen DatasetsCode1
Enhancing Speech Emotion Recognition Through Differentiable Architecture SearchCode1
Searching a Compact Architecture for Robust Multi-Exposure Image FusionCode1
GeNAS: Neural Architecture Search with Better GeneralizationCode1
HKNAS: Classification of Hyperspectral Imagery Based on Hyper Kernel Neural Architecture SearchCode1
Increasing the Scope as You Learn: Adaptive Bayesian Optimization in Nested SubspacesCode1
Can GPT-4 Perform Neural Architecture Search?Code1
Canvas: End-to-End Kernel Architecture Search in Neural NetworksCode1
ElasticViT: Conflict-aware Supernet Training for Deploying Fast Vision Transformer on Diverse Mobile DevicesCode1
SpaceEvo: Hardware-Friendly Search Space Design for Efficient INT8 InferenceCode1
MSINet: Twins Contrastive Search of Multi-Scale Interaction for Object ReIDCode1
Unified Functional Hashing in Automatic Machine LearningCode1
AutoPEFT: Automatic Configuration Search for Parameter-Efficient Fine-TuningCode1
ZiCo: Zero-shot NAS via Inverse Coefficient of Variation on GradientsCode1
Lightweight Neural Architecture Search for Temporal Convolutional Networks at the EdgeCode1
RD-NAS: Enhancing One-shot Supernet Ranking Ability via Ranking Distillation from Zero-cost ProxiesCode1
β-DARTS++: Bi-level Regularization for Proxy-robust Differentiable Architecture SearchCode1
HADAS: Hardware-Aware Dynamic Neural Architecture Search for Edge Performance ScalingCode1
AIO-P: Expanding Neural Performance Predictors Beyond Image ClassificationCode1
MPCViT: Searching for Accurate and Efficient MPC-Friendly Vision Transformer with Heterogeneous AttentionCode1
NAS-LID: Efficient Neural Architecture Search with Local Intrinsic DimensionCode1
Minimizing the Accumulated Trajectory Error to Improve Dataset DistillationCode1
Construction of Hierarchical Neural Architecture Search Spaces based on Context-free GrammarsCode1
Search to Pass Messages for Temporal Knowledge Graph CompletionCode1
Hierarchical quantum circuit representations for neural architecture searchCode1
Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face RecognitionCode1
Extensible Proxy for Efficient NASCode1
AutoMoE: Heterogeneous Mixture-of-Experts with Adaptive Computation for Efficient Neural Machine TranslationCode1
EC-NAS: Energy Consumption Aware Tabular Benchmarks for Neural Architecture SearchCode1
Demystifying Map Space Exploration for NPUsCode1
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All datasetsImageNetNAS-Bench-201, ImageNet-16-120CIFAR-10NAS-Bench-201, CIFAR-100NAS-Bench-201, CIFAR-10CIFAR-10 Image ClassificationCIFAR-100NATS-Bench Topology, CIFAR-10NATS-Bench Topology, CIFAR-100NATS-Bench Topology, ImageNet16-120Food-101NAS-Bench-101

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SPOS (ProxylessNAS (GPU) latency)Accuracy75.3—Unverified
2SPOS (FBNet-C latency)Accuracy75.1—Unverified
3SPOS (block search + channel search)Accuracy74.7—Unverified
4MUXNet-xsTop-1 Error Rate33.3—Unverified
5FBNetV2-F1Top-1 Error Rate31.7—Unverified
6LayerNAS-60MTop-1 Error Rate31—Unverified
7NASGEPTop-1 Error Rate29.51—Unverified
8MUXNet-sTop-1 Error Rate28.4—Unverified
9NN-MASS-ATop-1 Error Rate27.1—Unverified
10FBNetV2-F3Top-1 Error Rate26.8—Unverified
#ModelMetricClaimedVerifiedStatus
1CR-LSOAccuracy (Test)46.98—Unverified
2Shapley-NASAccuracy (Test)46.85—Unverified
3β-RDARTS-L2Accuracy (Test)46.71—Unverified
4β-SDARTS-RSAccuracy (Test)46.71—Unverified
5ASE-NAS+Accuracy (Val)46.66—Unverified
6NARAccuracy (Test)46.66—Unverified
7BaLeNAS-TFAccuracy (Test)46.54—Unverified
8AG-NetAccuracy (Test)46.42—Unverified
9Local searchAccuracy (Test)46.38—Unverified
10NASBOTAccuracy (Test)46.37—Unverified
#ModelMetricClaimedVerifiedStatus
1Balanced MixtureAccuracy (% )91.55—Unverified
2GDASTop-1 Error Rate3.4—Unverified
3Bonsai-NetTop-1 Error Rate3.35—Unverified
4Net2 (2)Top-1 Error Rate3.3—Unverified
5μDARTSTop-1 Error Rate3.28—Unverified
6NN-MASS- CIFAR-CTop-1 Error Rate3.18—Unverified
7NN-MASS- CIFAR-ATop-1 Error Rate3—Unverified
8DARTS (first order)Top-1 Error Rate3—Unverified
9NASGEPTop-1 Error Rate2.82—Unverified
10AlphaX-1 (cutout NASNet)Top-1 Error Rate2.82—Unverified