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 601–625 of 1915 papers

TitleStatusHype
AutoADR: Automatic Model Design for Ad Relevance—0
Chain-structured neural architecture search for financial time series forecasting—0
CE-NAS: An End-to-End Carbon-Efficient Neural Architecture Search Framework—0
AutoAdapt: Automated Segmentation Network Search for Unsupervised Domain Adaptation—0
All in One Bad Weather Removal Using Architectural Search—0
FAQS: Communication-efficient Federate DNN Architecture and Quantization Co-Search for personalized Hardware-aware Preferences—0
Causal-aware Graph Neural Architecture Search under Distribution Shifts—0
A Unified Deep Framework for Joint 3D Pose Estimation and Action Recognition from a Single RGB Camera—0
CATCH: Context-based Meta Reinforcement Learning for Transferrable Architecture Search—0
Cascaded Multi-task Adaptive Learning Based on Neural Architecture Search—0
A Little Bit Attention Is All You Need for Person Re-Identification—0
Cartesian Genetic Programming Approach for Designing Convolutional Neural Networks—0
Extensible and Efficient Proxy for Neural Architecture Search—0
Carbon Emissions and Large Neural Network Training—0
Combining Multi-Objective Bayesian Optimization with Reinforcement Learning for TinyML—0
FACETS: Efficient Once-for-all Object Detection via Constrained Iterative Search—0
Farthest Greedy Path Sampling for Two-shot Recommender Search—0
Carbon-Efficient Neural Architecture Search—0
AttentionSmithy: A Modular Framework for Rapid Transformer Development and Customization—0
AdaNAS: Adaptively Post-processing with Self-supervised Neural Architecture Search for Ensemble Rainfall Forecasts—0
Can weight sharing outperform random architecture search? An investigation with TuNAS—0
A Lightweight Neural Architecture Search Model for Medical Image Classification—0
Exploring Resiliency to Natural Image Corruptions in Deep Learning using Design Diversity—0
Can LLMs Revolutionize the Design of Explainable and Efficient TinyML Models?—0
A Transferable General-Purpose Predictor for Neural Architecture Search—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-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