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

Showing 101150 of 1915 papers

TitleStatusHype
SA-GNAS: Seed Architecture Expansion for Efficient Large-scale Graph Neural Architecture SearchCode0
ILASH: A Predictive Neural Architecture Search Framework for Multi-Task Applications0
GradAlign for Training-free Model Performance Inference0
Puzzle: Distillation-Based NAS for Inference-Optimized LLMs0
Knowledge-aware Evolutionary Graph Neural Architecture SearchCode0
A Graph Neural Architecture Search Approach for Identifying Bots in Social Media0
Fusion Matters: Learning Fusion in Deep Click-through Rate Prediction ModelsCode0
TSkips: Efficiency Through Explicit Temporal Delay Connections in Spiking Neural Networks0
GreenMachine: Automatic Design of Zero-Cost Proxies for Energy-Efficient NASCode0
Delta-NAS: Difference of Architecture Encoding for Predictor-based Evolutionary Neural Architecture Search0
Improving Routability Prediction via NAS Using a Smooth One-shot Augmented Predictor0
Data-to-Model Distillation: Data-Efficient Learning FrameworkCode0
Exploring the Manifold of Neural Networks Using Diffusion Geometry0
Retinal Vessel Segmentation via Neuron Programming0
RedTest: Towards Measuring Redundancy in Deep Neural Networks Effectively0
SASE: A Searching Architecture for Squeeze and Excitation Operations0
Zero-Shot NAS via the Suppression of Local Entropy Decrease0
Learning Morphisms with Gauss-Newton Approximation for Growing Networks0
Customized Subgraph Selection and Encoding for Drug-drug Interaction PredictionCode0
Differentiable architecture search with multi-dimensional attention for spiking neural networks0
Syno: Structured Synthesis for Neural Operators0
Hyperparameter Optimization in Machine Learning0
Yoga Pose Classification Using Transfer Learning0
Developing Convolutional Neural Networks using a Novel Lamarckian Co-Evolutionary Algorithm0
Towards Robust Out-of-Distribution Generalization: Data Augmentation and Neural Architecture Search Approaches0
Spatial-Temporal Search for Spiking Neural Networks0
MCUBERT: Memory-Efficient BERT Inference on Commodity Microcontrollers0
Neuroevolution Neural Architecture Search for Evolving RNNs in Stock Return Prediction and Portfolio Trading0
Mastering AI: Big Data, Deep Learning, and the Evolution of Large Language Models -- AutoML from Basics to State-of-the-Art Techniques0
Structure of Artificial Neural Networks -- Empirical Investigations0
ActNAS : Generating Efficient YOLO Models using Activation NAS0
DistDD: Distributed Data Distillation Aggregation through Gradient Matching0
On the Adversarial Transferability of Generalized "Skip Connections"Code0
Neural Architecture Search of Hybrid Models for NPU-CIM Heterogeneous AR/VR Devices0
Simultaneous Weight and Architecture Optimization for Neural NetworksCode0
Large Language Model Compression with Neural Architecture Search0
Automating Data Science Pipelines with Tensor CompletionCode0
Designing a Classifier for Active Fire Detection from Multispectral Satellite Imagery Using Neural Architecture Search0
MC-QDSNN: Quantized Deep evolutionary SNN with Multi-Dendritic Compartment Neurons for Stress Detection using Physiological Signals0
LPZero: Language Model Zero-cost Proxy Search from Zero0
Double Oracle Neural Architecture Search for Game Theoretic Deep Learning Models0
The OCON model: an old but gold solution for distributable supervised classificationCode0
The OCON model: an old but green solution for distributable supervised classification for acoustic monitoring in smart cities0
Resource-aware Mixed-precision Quantization for Enhancing Deployability of Transformers for Time-series Forecasting on Embedded FPGAs0
Scalable Reinforcement Learning-based Neural Architecture Search0
Cartesian Genetic Programming Approach for Designing Convolutional Neural Networks0
Lightweight Neural Architecture Search for Cerebral Palsy DetectionCode0
POMONAG: Pareto-Optimal Many-Objective Neural Architecture Generator0
RNC: Efficient RRAM-aware NAS and Compilation for DNNs on Resource-Constrained Edge DevicesCode0
Optimistic Games for Combinatorial Bayesian Optimization with Application to Protein Design0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SPOS (ProxylessNAS (GPU) latency)Accuracy75.3Unverified
2SPOS (FBNet-C latency)Accuracy75.1Unverified
3SPOS (block search + channel search)Accuracy74.7Unverified
4MUXNet-xsTop-1 Error Rate33.3Unverified
5FBNetV2-F1Top-1 Error Rate31.7Unverified
6LayerNAS-60MTop-1 Error Rate31Unverified
7NASGEPTop-1 Error Rate29.51Unverified
8MUXNet-sTop-1 Error Rate28.4Unverified
9NN-MASS-ATop-1 Error Rate27.1Unverified
10FBNetV2-F3Top-1 Error Rate26.8Unverified
#ModelMetricClaimedVerifiedStatus
1CR-LSOAccuracy (Test)46.98Unverified
2Shapley-NASAccuracy (Test)46.85Unverified
3β-RDARTS-L2Accuracy (Test)46.71Unverified
4β-SDARTS-RSAccuracy (Test)46.71Unverified
5ASE-NAS+Accuracy (Val)46.66Unverified
6NARAccuracy (Test)46.66Unverified
7BaLeNAS-TFAccuracy (Test)46.54Unverified
8AG-NetAccuracy (Test)46.42Unverified
9Local searchAccuracy (Test)46.38Unverified
10NASBOTAccuracy (Test)46.37Unverified
#ModelMetricClaimedVerifiedStatus
1Balanced MixtureAccuracy (% )91.55Unverified
2GDASTop-1 Error Rate3.4Unverified
3Bonsai-NetTop-1 Error Rate3.35Unverified
4Net2 (2)Top-1 Error Rate3.3Unverified
5μDARTSTop-1 Error Rate3.28Unverified
6NN-MASS- CIFAR-CTop-1 Error Rate3.18Unverified
7NN-MASS- CIFAR-ATop-1 Error Rate3Unverified
8DARTS (first order)Top-1 Error Rate3Unverified
9NASGEPTop-1 Error Rate2.82Unverified
10AlphaX-1 (cutout NASNet)Top-1 Error Rate2.82Unverified