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 651–700 of 1915 papers

TitleStatusHype
Tackling Neural Architecture Search With Quality Diversity OptimizationCode0
Evaluating the Practicality of Learned Image Compression—0
Neural Architecture Search on Efficient Transformers and Beyond—0
ALBench: A Framework for Evaluating Active Learning in Object DetectionCode2
Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-ResolutionCode1
Guided Evolutionary Neural Architecture Search With Efficient Performance Estimation—0
Hyper-Representations for Pre-Training and Transfer LearningCode1
Efficient Search of Multiple Neural Architectures with Different Complexities via Importance Sampling—0
DC-BENCH: Dataset Condensation BenchmarkCode1
EASNet: Searching Elastic and Accurate Network Architecture for Stereo MatchingCode0
Improving Neural Architecture Search by Mixing a FireFly algorithm with a Training Free EvaluationCode0
CLOSE: Curriculum Learning On the Sharing Extent Towards Better One-shot NAS—0
PASHA: Efficient HPO and NAS with Progressive Resource AllocationCode0
NASRec: Weight Sharing Neural Architecture Search for Recommender SystemsCode1
MRF-UNets: Searching UNet with Markov Random FieldsCode0
Graph Property Prediction on Open Graph Benchmark: A Winning Solution by Graph Neural Architecture SearchCode1
UniNet: Unified Architecture Search with Convolution, Transformer, and MLPCode1
Bi-fidelity Evolutionary Multiobjective Search for Adversarially Robust Deep Neural Architectures—0
Long-term Reproducibility for Neural Architecture SearchCode0
Noisy Heuristics NAS: A Network Morphism based Neural Architecture Search using HeuristicsCode0
SuperTickets: Drawing Task-Agnostic Lottery Tickets from Supernets via Jointly Architecture Searching and Parameter PruningCode1
Betty: An Automatic Differentiation Library for Multilevel Optimization—0
FlowNAS: Neural Architecture Search for Optical Flow EstimationCode1
Architecture Augmentation for Performance Predictor Based on Graph Isomorphism—0
Tree ensemble kernels for Bayesian optimization with known constraints over mixed-feature spacesCode0
Multi-scale Attentive Image De-raining Networks via Neural Architecture SearchCode0
Multi-Prior Learning via Neural Architecture Search for Blind Face RestorationCode1
Quantum Neural Architecture Search with Quantum Circuits Metric and Bayesian Optimization—0
Prior-Guided One-shot Neural Architecture SearchCode1
FEATHERS: Federated Architecture and Hyperparameter Search—0
Conformer Based Elderly Speech Recognition System for Alzheimer's Disease Detection—0
FedorAS: Federated Architecture Search under system heterogeneity—0
Survival Kernets: Scalable and Interpretable Deep Kernel Survival Analysis with an Accuracy GuaranteeCode0
Shapley-NAS: Discovering Operation Contribution for Neural Architecture SearchCode1
NAS-Bench-Graph: Benchmarking Graph Neural Architecture SearchCode1
FreeREA: Training-Free Evolution-based Architecture SearchCode1
DFG-NAS: Deep and Flexible Graph Neural Architecture SearchCode0
Channel-wise Mixed-precision Assignment for DNN Inference on Constrained Edge NodesCode0
Neural Architecture Adaptation for Object Detection by Searching Channel Dimensions and Mapping Pre-trained Parameters—0
ERNAS: An Evolutionary Neural Architecture Search for Magnetic Resonance Image Reconstructions—0
Improve Ranking Correlation of Super-net through Training Scheme from One-shot NAS to Few-shot NASCode0
EmProx: Neural Network Performance Estimation For Neural Architecture SearchCode0
Exploring the Intersection between Neural Architecture Search and Continual Learning—0
SDQ: Stochastic Differentiable Quantization with Mixed Precision—0
Neural Prompt SearchCode2
Towards Self-supervised and Weight-preserving Neural Architecture SearchCode0
RT-DNAS: Real-time Constrained Differentiable Neural Architecture Search for 3D Cardiac Cine MRI Segmentation—0
TransBO: Hyperparameter Optimization via Two-Phase Transfer Learning—0
Transfer Learning based Search Space Design for Hyperparameter Tuning—0
AGNAS: Attention-Guided Micro- and Macro-Architecture SearchCode0
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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