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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1001–1050 of 1915 papers

TitleStatusHype
Warm-starting DARTS using meta-learning—0
Deep Architecture Connectivity Matters for Its Convergence: A Fine-Grained AnalysisCode0
AutoLC: Search Lightweight and Top-Performing Architecture for Remote Sensing Image Land-Cover ClassificationCode0
Neural Architecture Search using Property Guided Synthesis—0
A Collaboration Strategy in the Mining Pool for Proof-of-Neural-Architecture Consensus—0
Gait Recognition in the Wild: A Large-scale Benchmark and NAS-based BaselineCode0
UnrealNAS: Can We Search Neural Architectures with Unreal Data?—0
Local Stochastic Bilevel Optimization with Momentum-Based Variance Reduction—0
Self-Programming Artificial Intelligence Using Code-Generating Language Models—0
Reducing Neural Architecture Search Spaces with Training-Free Statistics and Computational Graph Clustering—0
MAPLE-Edge: A Runtime Latency Predictor for Edge Devices—0
PRE-NAS: Predictor-assisted Evolutionary Neural Architecture Search—0
GPUNet: Searching the Deployable Convolution Neural Networks for GPUs—0
Enable Deep Learning on Mobile Devices: Methods, Systems, and Applications—0
PVNAS: 3D Neural Architecture Search with Point-Voxel Convolution—0
Adaptive hybrid activation function for deep neural networksCode0
Towards Privacy-Preserving Neural Architecture Search—0
SpiderNet: Hybrid Differentiable-Evolutionary Architecture Search via Train-Free MetricsCode0
TabNAS: Rejection Sampling for Neural Architecture Search on Tabular DatasetsCode0
HASA: Hybrid Architecture Search with Aggregation Strategy for Echinococcosis Classification and Ovary Segmentation in Ultrasound Images—0
Efficient Re-parameterization Operations Search for Easy-to-Deploy Network Based on Directional Evolutionary Strategy—0
Arch-Graph: Acyclic Architecture Relation Predictor for Task-Transferable Neural Architecture SearchCode0
When NAS Meets Trees: An Efficient Algorithm for Neural Architecture SearchCode0
SplitNets: Designing Neural Architectures for Efficient Distributed Computing on Head-Mounted Systems—0
Searching for Efficient Neural Architectures for On-Device ML on Edge TPUs—0
A Survey of Supernet Optimization and its Applications: Spatial and Temporal Optimization for Neural Architecture Search—0
ShiftNAS: Towards Automatic Generation of Advanced Mulitplication-Less Neural Networks—0
Bridging the Gap of AutoGraph between Academia and Industry: Analysing AutoGraph Challenge at KDD Cup 2020Code0
i-Razor: A Differentiable Neural Input Razor for Feature Selection and Dimension Search in DNN-Based Recommender SystemsCode0
Novelty Driven Evolutionary Neural Architecture SearchCode0
Neural Architecture Search for Speech Emotion Recognition—0
Quasi-orthogonality and intrinsic dimensions as measures of learning and generalisation—0
AutoCoMet: Smart Neural Architecture Search via Co-Regulated Shaping Reinforcement—0
Demystifying the Neural Tangent Kernel from a Practical Perspective: Can it be trusted for Neural Architecture Search without training?Code0
Robust and Energy-efficient PPG-based Heart-Rate Monitoring—0
AutoTS: Automatic Time Series Forecasting Model Design Based on Two-Stage Pruning—0
EmotionNAS: Two-stream Neural Architecture Search for Speech Emotion Recognition—0
An Intelligent End-to-End Neural Architecture Search Framework for Electricity Forecasting Model Development—0
A Semi-Decoupled Approach to Fast and Optimal Hardware-Software Co-Design of Neural AcceleratorsCode0
U-Boost NAS: Utilization-Boosted Differentiable Neural Architecture SearchCode0
Progressive Subsampling for Oversampled Data -- Application to Quantitative MRICode0
On Redundancy and Diversity in Cell-based Neural Architecture SearchCode0
Meta-Learning of NAS for Few-shot Learning in Medical Image Applications—0
Less is More: Proxy Datasets in NAS approachesCode0
TAS: Ternarized Neural Architecture Search for Resource-Constrained Edge DevicesCode0
Towards Bi-directional Skip Connections in Encoder-Decoder Architectures and Beyond—0
Multi-trial Neural Architecture Search with Lottery Tickets—0
A^3D: A Platform of Searching for Robust Neural Architectures and Efficient Adversarial Attacks—0
WPNAS: Neural Architecture Search by jointly using Weight Sharing and Predictor—0
Improving the Energy Efficiency and Robustness of tinyML Computer Vision using Log-Gradient Input Images—0
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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