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 1551–1600 of 1915 papers

TitleStatusHype
An ENAS Based Approach for Constructing Deep Learning Models for Breast Cancer Recognition from Ultrasound Images—0
An Empirical Study on Regularization of Deep Neural Networks by Local Rademacher Complexity—0
An Empirical Exploration of Deep Recurrent Connections and Memory Cells Using Neuro-Evolution—0
Rethinking Co-design of Neural Architectures and Hardware Accelerators—0
An Efficient NAS-based Approach for Handling Imbalanced Datasets—0
Neural Architecture Search using Property Guided Synthesis—0
An Approach for Efficient Neural Architecture Search Space Definition—0
Rethinking the Number of Channels for the Convolutional Neural Network—0
A Comprehensive Survey on Hardware-Aware Neural Architecture Search—0
Retinal Vessel Segmentation via Neuron Programming—0
Revealing the Invisible with Model and Data Shrinking for Composite-database Micro-expression Recognition—0
MAE-DET: Revisiting Maximum Entropy Principle in Zero-Shot NAS for Efficient Object Detection—0
Revisiting Learning-based Video Motion Magnification for Real-time Processing—0
XferNAS: Transfer Neural Architecture Search—0
Revisiting Neural Architecture Search—0
An Approach for Combining Multimodal Fusion and Neural Architecture Search Applied to Knowledge Tracing—0
A Comprehensive Survey of Neural Architecture Search: Challenges and Solutions—0
Revisiting the Train Loss: an Efficient Performance Estimator for Neural Architecture Search—0
AACP: Model Compression by Accurate and Automatic Channel Pruning—0
RHNAS: Realizable Hardware and Neural Architecture Search—0
An Analysis of Super-Net Heuristics in Weight-Sharing NAS—0
Analyzing and Mitigating Interference in Neural Architecture Search—0
RNAS-CL: Robust Neural Architecture Search by Cross-Layer Knowledge Distillation—0
XploreNAS: Explore Adversarially Robust & Hardware-efficient Neural Architectures for Non-ideal Xbars—0
Robust 3D Face Alignment with Multi-Path Neural Architecture Search—0
Robust and Energy-efficient PPG-based Heart-Rate Monitoring—0
Analyzing the Expected Hitting Time of Evolutionary Computation-based Neural Architecture Search Algorithms—0
A Multi-criteria Approach to Evolve Sparse Neural Architectures for Stock Market Forecasting—0
Robust NAS under adversarial training: benchmark, theory, and beyond—0
Robust Neural Architecture Search—0
Trends in Neural Architecture Search: Towards the Acceleration of Search—0
ROME: Robustifying Memory-Efficient NAS via Topology Disentanglement and Gradient Accumulation—0
RSBNet: One-Shot Neural Architecture Search for A Backbone Network in Remote Sensing Image Recognition—0
RT-DNAS: Real-time Constrained Differentiable Neural Architecture Search for 3D Cardiac Cine MRI Segmentation—0
RT-RCG: Neural Network and Accelerator Search Towards Effective and Real-time ECG Reconstruction from Intracardiac Electrograms—0
S2DNAS:Transforming Static CNN Model for Dynamic Inference via Neural Architecture Search—0
S2DNAS: Transforming Static CNN Model for Dynamic Inference via Neural Architecture Search—0
AMLA: an AutoML frAmework for Neural Network Design—0
Trilevel Neural Architecture Search for Efficient Single Image Super-Resolution—0
Triple Path Enhanced Neural Architecture Search for Multimodal Fake News Detection—0
Saliency-Aware Neural Architecture Search—0
TripLe: Revisiting Pretrained Model Reuse and Progressive Learning for Efficient Vision Transformer Scaling and Searching—0
Sampled Training and Node Inheritance for Fast Evolutionary Neural Architecture Search—0
Sample-Efficient "Clustering and Conquer" Procedures for Parallel Large-Scale Ranking and Selection—0
Sample-Efficient Neural Architecture Search by Learning Action Space—0
Sample-Efficient Neural Architecture Search by Learning Action Space for Monte Carlo Tree Search—0
SpiKernel: A Kernel Size Exploration Methodology for Improving Accuracy of the Embedded Spiking Neural Network Systems—0
SASE: A Searching Architecture for Squeeze and Excitation Operations—0
Scalable NAS with Factorizable Architectural Parameters—0
Scalable Neural Architecture Search for 3D Medical Image Segmentation—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