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 1401–1425 of 1915 papers

TitleStatusHype
Joint Learning of Neural Transfer and Architecture Adaptation for Image Recognition—0
Joint Neural Architecture Search and Quantization—0
Katib: A Distributed General AutoML Platform on Kubernetes—0
Kernel-Level Energy-Efficient Neural Architecture Search for Tabular Dataset—0
Knowledge Distillation: A Survey—0
L^2NAS: Learning to Optimize Neural Architectures via Continuous-Action Reinforcement Learning—0
Landscape of Neural Architecture Search across sensors: how much do they differ ?—0
Large Scale Neural Architecture Search with Polyharmonic Splines—0
Latency-Aware Neural Architecture Search with Multi-Objective Bayesian Optimization—0
Latency-Controlled Neural Architecture Search for Streaming Speech Recognition—0
LayerNAS: Neural Architecture Search in Polynomial Complexity—0
LC-NAS: Latency Constrained Neural Architecture Search for Point Cloud Networks—0
Learned Transferable Architectures Can Surpass Hand-Designed Architectures for Large Scale Speech Recognition—0
Learning a Data-Driven Policy Network for Pre-Training Automated Feature Engineering—0
Learning Architectures from an Extended Search Space for Language Modeling—0
Learning by Grouping: A Multilevel Optimization Framework for Improving Fairness in Classification without Losing Accuracy—0
Learning by Passing Tests, with Application to Neural Architecture Search—0
Learning by Self-Explanation, with Application to Neural Architecture Search—0
Learning by Teaching, with Application to Neural Architecture Search—0
Learning Effective and Efficient Embedding via an Adaptively-Masked Twins-based Layer—0
Learning Efficient Image Super-Resolution Networks via Structure-Regularized Pruning—0
Learning from Mistakes based on Class Weighting with Application to Neural Architecture Search—0
Learning Graph Representation of Person-specific Cognitive Processes from Audio-visual Behaviours for Automatic Personality Recognition—0
Learning Language-Specific Layers for Multilingual Machine Translation—0
Learning Latent Architectural Distribution in Differentiable Neural Architecture Search via Variational Information Maximization—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