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 551–600 of 1915 papers

TitleStatusHype
HGNAS: Hardware-Aware Graph Neural Architecture Search for Edge Devices—0
Design Principle Transfer in Neural Architecture Search via Large Language ModelsCode0
NEAR: A Training-Free Pre-Estimator of Machine Learning Model PerformanceCode0
Neural Architecture Search based Global-local Vision Mamba for Palm-Vein Recognition—0
Evolutionary Neural Architecture Search for 3D Point Cloud Analysis—0
Combining Neural Architecture Search and Automatic Code Optimization: A Survey—0
TopoNAS: Boosting Search Efficiency of Gradient-based NAS via Topological Simplification—0
AutoPV: Automatically Design Your Photovoltaic Power Forecasting Model—0
Efficient Multi-Objective Neural Architecture Search via Pareto Dominance-based Novelty Search—0
SalNAS: Efficient Saliency-prediction Neural Architecture Search with self-knowledge distillationCode0
Comprehensive Study on Performance Evaluation and Optimization of Model Compression: Bridging Traditional Deep Learning and Large Language Models—0
A Pairwise Comparison Relation-assisted Multi-objective Evolutionary Neural Architecture Search Method with Multi-population Mechanism—0
Data-Algorithm-Architecture Co-Optimization for Fair Neural Networks on Skin Lesion Dataset—0
MO-EMT-NAS: Multi-Objective Continuous Transfer of Architectural Knowledge Between Tasks from Different Datasets—0
MCU-MixQ: A HW/SW Co-optimized Mixed-precision Neural Network Design Framework for MCUs—0
DDFAD: Dataset Distillation Framework for Audio Data—0
SliceMamba with Neural Architecture Search for Medical Image Segmentation—0
HCS-TNAS: Hybrid Constraint-driven Semi-supervised Transformer-NAS for Ultrasound Image Segmentation—0
CLASH: Complementary Learning with Neural Architecture Search for Gait Recognition—0
ShiftAddAug: Augment Multiplication-Free Tiny Neural Network with Hybrid Computation—0
Accelerate Intermittent Deep Inference—0
NeuroNAS: Enhancing Efficiency of Neuromorphic In-Memory Computing for Intelligent Mobile Agents through Hardware-Aware Spiking Neural Architecture Search—0
Towards Lightweight Graph Neural Network Search with Curriculum Graph Sparsification—0
An Efficient NAS-based Approach for Handling Imbalanced Datasets—0
Behaviour DistillationCode0
Straight Through Gumbel Softmax Estimator based Bimodal Neural Architecture Search for Audio-Visual Deepfake Detection—0
Additive regularization schedule for neural architecture search—0
Robust 3D Face Alignment with Multi-Path Neural Architecture Search—0
Heterogeneous Learning Rate Scheduling for Neural Architecture Search on Long-Tailed Datasets—0
Multi-Objective Neural Architecture Search for In-Memory Computing—0
Reinforced Compressive Neural Architecture Search for Versatile Adversarial Robustness—0
Large Language Model Assisted Adversarial Robustness Neural Architecture SearchCode0
Optimizing Time Series Forecasting Architectures: A Hierarchical Neural Architecture Search Approach—0
BEACON: A Bayesian Optimization Strategy for Novelty Search in Expensive Black-Box Systems—0
CAP: A Context-Aware Neural Predictor for NASCode0
Can Dense Connectivity Benefit Outlier Detection? An Odyssey with NAS—0
Towards Neural Architecture Search for Transfer Learning in 6G Networks—0
Fruit Classification System with Deep Learning and Neural Architecture Search—0
CE-NAS: An End-to-End Carbon-Efficient Neural Architecture Search Framework—0
Pretrained Hybrids with MAD Skills—0
Multi-Objective Neural Architecture Search by Learning Search Space Partitions—0
GI-NAS: Boosting Gradient Inversion Attacks through Adaptive Neural Architecture Search—0
Sheaf HyperNetworks for Personalized Federated Learning—0
LLaMA-NAS: Efficient Neural Architecture Search for Large Language Models—0
Efficient Visual Fault Detection for Freight Train via Neural Architecture Search with Data Volume Robustness—0
The devil is in discretization discrepancy. Robustifying Differentiable NAS with Single-Stage Searching Protocol—0
Causal-aware Graph Neural Architecture Search under Distribution Shifts—0
Moreau Envelope for Nonconvex Bi-Level Optimization: A Single-loop and Hessian-free Solution Strategy—0
Generative flow induced neural architecture search: Towards discovering optimal architecture in wavelet neural operator—0
GRASP-GCN: Graph-Shape Prioritization for Neural Architecture Search under Distribution Shifts—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