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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 251–300 of 1915 papers

TitleStatusHype
Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary CellsCode1
Optimal Subarchitecture Extraction For BERTCode1
AutoSNN: Towards Energy-Efficient Spiking Neural NetworksCode1
Overcoming Multi-Model Forgetting in One-Shot NAS With Diversity MaximizationCode1
Block-Wisely Supervised Neural Architecture Search With Knowledge DistillationCode1
Evolutionary Neural Cascade Search across SupernetworksCode1
Blockwisely Supervised Neural Architecture Search with Knowledge DistillationCode1
BiX-NAS: Searching Efficient Bi-directional Architecture for Medical Image SegmentationCode1
Evolutionary Neural Architecture Search for Transformer in Knowledge TracingCode1
Evolving Search Space for Neural Architecture SearchCode1
Bounce: Reliable High-Dimensional Bayesian Optimization for Combinatorial and Mixed SpacesCode1
Evolutionary Neural AutoML for Deep LearningCode1
Adjoined Networks: A Training Paradigm with Applications to Network CompressionCode1
BN-NAS: Neural Architecture Search with Batch NormalizationCode1
BM-NAS: Bilevel Multimodal Neural Architecture SearchCode1
Exploring Relational Context for Multi-Task Dense PredictionCode1
AdvRush: Searching for Adversarially Robust Neural ArchitecturesCode1
FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture SearchCode1
FEAR: A Simple Lightweight Method to Rank ArchitecturesCode1
Bag of Baselines for Multi-objective Joint Neural Architecture Search and Hyperparameter OptimizationCode1
Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum SearchCode1
BSQ: Exploring Bit-Level Sparsity for Mixed-Precision Neural Network QuantizationCode1
FlowNAS: Neural Architecture Search for Optical Flow EstimationCode1
FNA++: Fast Network Adaptation via Parameter Remapping and Architecture SearchCode1
CLEARER: Multi-Scale Neural Architecture Search for Image RestorationCode1
BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture SearchCode1
Adversarial Branch Architecture Search for Unsupervised Domain AdaptationCode1
AutoSpeech: Neural Architecture Search for Speaker RecognitionCode1
Can GPT-4 Perform Neural Architecture Search?Code1
Generalizing Few-Shot NAS with Gradient MatchingCode1
Hierarchical quantum circuit representations for neural architecture searchCode1
Canvas: End-to-End Kernel Architecture Search in Neural NetworksCode1
ChamNet: Towards Efficient Network Design through Platform-Aware Model AdaptationCode1
GLiT: Neural Architecture Search for Global and Local Image TransformerCode1
CATE: Computation-aware Neural Architecture Encoding with TransformersCode1
G-NAS: Generalizable Neural Architecture Search for Single Domain Generalization Object DetectionCode1
AFter: Attention-based Fusion Router for RGBT TrackingCode1
Bayesian Model Selection, the Marginal Likelihood, and GeneralizationCode1
Bayesian Neural Architecture Search using A Training-Free Performance MetricCode1
Are Labels Necessary for Neural Architecture Search?Code1
ColdNAS: Search to Modulate for User Cold-Start RecommendationCode1
β-DARTS: Beta-Decay Regularization for Differentiable Architecture SearchCode1
b-DARTS: Beta-Decay Regularization for Differentiable Architecture SearchCode1
β-DARTS++: Bi-level Regularization for Proxy-robust Differentiable Architecture SearchCode1
BigNAS: Scaling Up Neural Architecture Search with Big Single-Stage ModelsCode1
Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-ResolutionCode1
Contrastive Neural Architecture Search with Neural Architecture ComparatorsCode1
Hierarchical Neural Architecture Search for Single Image Super-ResolutionCode1
Contrastive Embeddings for Neural ArchitecturesCode1
DARTS-: Robustly Stepping out of Performance Collapse Without IndicatorsCode1
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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-SDARTS-RSAccuracy (Test)46.71—Unverified
4β-RDARTS-L2Accuracy (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
7DARTS (first order)Top-1 Error Rate3—Unverified
8NN-MASS- CIFAR-ATop-1 Error Rate3—Unverified
9AlphaX-1 (cutout NASNet)Top-1 Error Rate2.82—Unverified
10NASGEPTop-1 Error Rate2.82—Unverified