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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 201–250 of 1915 papers

TitleStatusHype
Robust 3D Face Alignment with Multi-Path Neural Architecture Search—0
Heterogeneous Learning Rate Scheduling for Neural Architecture Search on Long-Tailed Datasets—0
Reinforced Compressive Neural Architecture Search for Versatile Adversarial Robustness—0
Multi-Objective Neural Architecture Search for In-Memory Computing—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
Combinatorial Optimization with Automated Graph Neural NetworksCode2
CAP: A Context-Aware Neural Predictor for NASCode0
Can Dense Connectivity Benefit Outlier Detection? An Odyssey with NAS—0
Fruit Classification System with Deep Learning and Neural Architecture Search—0
Towards Neural Architecture Search for Transfer Learning in 6G Networks—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
einspace: Searching for Neural Architectures from Fundamental OperationsCode1
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
HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language ModelsCode1
Moreau Envelope for Nonconvex Bi-Level Optimization: A Single-loop and Hessian-free Solution Strategy—0
Differentiable Model Scaling using Differentiable TopkCode1
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
Hard Work Does Not Always Pay Off: Poisoning Attacks on Neural Architecture Search—0
Aux-NAS: Exploiting Auxiliary Labels with Negligibly Extra Inference CostCode0
Towards Accurate and Robust Architectures via Neural Architecture Search—0
A method for quantifying the generalization capabilities of generative models for solving Ising models—0
Implantable Adaptive Cells: differentiable architecture search to improve the performance of any trained U-shaped networkCode0
A Lightweight Neural Architecture Search Model for Medical Image Classification—0
AFter: Attention-based Fusion Router for RGBT TrackingCode1
Structural Pruning of Pre-trained Language Models via Neural Architecture SearchCode0
Graph is all you need? Lightweight data-agnostic neural architecture search without training—0
ATOM: Attention Mixer for Efficient Dataset DistillationCode0
CSCO: Connectivity Search of Convolutional OperatorsCode0
Surprisingly Strong Performance Prediction with Neural Graph FeaturesCode0
A Multi-objective Optimization Benchmark Test Suite for Real-time Semantic SegmentationCode2
FR-NAS: Forward-and-Reverse Graph Predictor for Efficient Neural Architecture SearchCode1
Efficient NAS with FaDE on Hierarchical Spaces—0
Identifying phase transitions in physical systems with neural networks: a neural architecture search perspective—0
Unsupervised Domain Adaptation Architecture Search with Self-Training for Land Cover MappingCode0
Rapid Deployment of DNNs for Edge Computing via Structured Pruning at Initialization—0
Shears: Unstructured Sparsity with Neural Low-rank Adapter SearchCode0
MobileNetV4 -- Universal Models for the Mobile EcosystemCode3
Network architecture search of X-ray based scientific applications—0
Differentiable Search for Finding Optimal Quantization Strategy—0
Accel-NASBench: Sustainable Benchmarking for Accelerator-Aware NASCode0
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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