AutoML info

and AutoML Freiburg-Hannover

What’s the deal with Neural Architecture Search?

Google Could AutoML

and PocketFlow

In Defense of Weight-sharing for Neural Architecture Search: an optimization perspective

PyGlove

NASLib

Keras Tuner

NNI

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning. (archived)

AutoGluon

is toolkit for Deep learning that automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few lines of code, you can train and deploy high-accuracy deep learning models on tabular, image, and text data.

Auto-PyTorch

Automatic architecture search and hyperparameter optimization for PyTorch.

AutoDL-Projects

aw_nas

Determined

Deep learning training platform with integrated support for distributed training, hyperparameter tuning, smart GPU scheduling, experiment tracking, and a model registry.

TPOT

Tool that automatically creates and optimizes machine learning pipelines using genetic programming. Consider it your personal data science assistant, automating a tedious part of machine learning.

NAS-Bench-101: Towards Reproducible Neural Architecture Search

ICML 2019

NAS-Bench-201: Extending the Scope of Reproducible Neural Architecture Search

ICLR 2020

NAS-Bench-301 and the Case for Surrogate Benchmarks for Neural Architecture Search

arXiv 2020

NAS-Bench-1Shot1: Benchmarking and Dissecting One-shot Neural Architecture Search

ICLR 2020

NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size

TPAMI 2021

NAS-Bench-ASR: Reproducible Neural Architecture Search for Speech Recognition

ICLR 2021

HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark

ICLR 2021

NAS-Bench-NLP: Neural Architecture Search Benchmark for Natural Language Processing

arXiv 2020

NAS-Bench-x11 and the Power of Learning Curves

NeurIPS 2021

CATE: Computation-aware Neural Architecture Encoding with Transformers

ICML

Searching by Generating: Flexible and Efficient One-Shot NAS with Architecture Generator

CVPR

Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition

ICCV

AutoFormer: Searching Transformers for Visual Recognition

ICCV

LightTrack: Finding Lightweight Neural Networks for Object Tracking via One-Shot Architecture Search

CVPR

One-Shot Neural Ensemble Architecture Search by Diversity-Guided Search Space Shrinking

CVPR

DARTS-: Robustly Stepping out of Performance Collapse Without Indicators

ICLR

Zero-Cost Proxies for Lightweight NAS

ICLR

Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective

ICLR

DrNAS: Dirichlet Neural Architecture Search

ICLR

Rethinking Architecture Selection in Differentiable NAS

ICLR

Evolving Reinforcement Learning Algorithms

ICLR

AutoHAS: Differentiable Hyper-parameter and Architecture Search

ICLR-W

FBNetV3: Joint Architecture-Recipe Search using Neural Acquisition Function

CVPR

Cream of the Crop: Distilling Prioritized Paths For One-Shot Neural Architecture Search

NeurIPS

PyGlove

Does Unsupervised Architecture Representation Learning Help Neural Architecture Search

NeurIPS

RandAugment: Practical Automated Data Augmentation with a Reduced Search Space

NeurIPS

Delta-STN: Efficient Bilevel Optimization for Neural Networks using Structured Response Jacobians

NeurIPS

A Study on Encodings for Neural Architecture Search

NeurIPS

AutoBSS: An Efficient Algorithm for Block Stacking Style Search

NeurIPS

Bridging the Gap between Sample-based and One-shot Neural Architecture Search with BONAS

NeurIPS

Interstellar: Searching Recurrent Architecture for Knowledge Graph Embedding

NeurIPS

Revisiting Parameter Sharing for Automatic Neural Channel Number Search

NeurIPS

Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search

NeurIPS

Neural Architecture Search using Deep Neural Networks and Monte Carlo Tree Search

AAAI

Representation Sharing for Fast Object Detector Search and Beyond

ECCV

Are Labels Necessary for Neural Architecture Search?

ECCV

Single Path One-Shot Neural Architecture Search with Uniform Sampling

ECCV

Neural Predictor for Neural Architecture Search

ECCV

BigNAS: Scaling Up Neural Architecture Search with Big Single-Stage Models

ECCV

BATS: Binary ArchitecTure Search

ECCV

AttentionNAS: Spatiotemporal Attention Cell Search for Video Classification

ECCV

Search What You Want: Barrier Panelty NAS for Mixed Precision Quantization

ECCV

Angle-based Search Space Shrinking for Neural Architecture Search

ECCV

Anti-Bandit Neural Architecture Search for Model Defense

ECCV

TF-NAS: Rethinking Three Search Freedoms of Latency-Constrained Differentiable Neural Architecture Search

ECCV

Fair DARTS: Eliminating Unfair Advantages in Differentiable Architecture Search

ECCV

Off-Policy Reinforcement Learning for Efficient and Effective GAN Architecture Search

ECCV

DA-NAS: Data Adapted Pruning for Efficient Neural Architecture Search

ECCV

Optimizing Millions of Hyperparameters by Implicit Differentiation

AISTATS

Evolving Machine Learning Algorithms From Scratch

ICML

Stabilizing Differentiable Architecture Search via Perturbation-based Regularization

ICML

NADS: Neural Architecture Distribution Search for Uncertainty Awareness

ICML

Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data

ICML

Hit-Detector: Hierarchical Trinity Architecture Search for Object Detection

CVPR

Designing Network Design Spaces

CVPR

UNAS: Differentiable Architecture Search Meets Reinforcement Learning

CVPR

MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation

CVPR

A Semi-Supervised Assessor of Neural Architectures

CVPR

Binarizing MobileNet via Evolution-based Searching

CVPR

Rethinking Performance Estimation in Neural Architecture Search

CVPR

APQ: Joint Search for Network Architecture, Pruning and Quantization Policy

CVPR

SGAS: Sequential Greedy Architecture Search

CVPR

Can Weight Sharing Outperform Random Architecture Search? An Investigation With TuNAS

CVPR

FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions

CVPR

AdversarialNAS: Adversarial Neural Architecture Search for GANs

CVPR

When NAS Meets Robustness: In Search of Robust Architectures against Adversarial Attacks

CVPR

Block-wisely Supervised Neural Architecture Search with Knowledge Distillation

CVPR

Overcoming Multi-Model Forgetting in One-Shot NAS with Diversity Maximization

CVPR

Densely Connected Search Space for More Flexible Neural Architecture Search

CVPR

EfficientDet: Scalable and Efficient Object Detection

CVPR

NAS-Bench-201: Extending the Scope of Reproducible Neural Architecture Search

ICLR 2020

Understanding Architectures Learnt by Cell-based Neural Architecture Search

ICLR

Evaluating The Search Phase of Neural Architecture Search

ICLR

AtomNAS: Fine-Grained End-to-End Neural Architecture Search

ICLR

Fast Neural Network Adaptation via Parameter Remapping and Architecture Search

ICLR

Once for All: Train One Network and Specialize it for Efficient Deployment

ICLR

PC-DARTS: Partial Channel Connections for Memory-Efficient Architecture Search

ICLR

NAS evaluation is frustratingly hard

ICLR

FasterSeg: Searching for Faster Real-time Semantic Segmentation

ICLR

Computation Reallocation for Object Detection

ICLR

Towards Fast Adaptation of Neural Architectures with Meta Learning

ICLR

AssembleNet: Searching for Multi-Stream Neural Connectivity in Video Architectures

ICLR

Fast, Accurate and Lightweight Super-Resolution with Neural Architecture Search

ICPR

Self-Tuning Networks: Bilevel Optimization of Hyperparameters using Structured Best-Response Functions

ICLR

DATA: Differentiable ArchiTecture Approximation

NeurIPS

Random Search and Reproducibility for Neural Architecture Search

UAI

Improved Differentiable Architecture Search for Language Modeling and Named Entity Recognition

EMNLP

Continual and Multi-Task Architecture Search

ACL

Progressive Differentiable Architecture Search: Bridging the Depth Gap Between Search and Evaluation

ICCV

Multinomial Distribution Learning for Effective Neural Architecture Search

ICCV

Searching for MobileNetV3

ICCV

Multinomial Distribution Learning for Effective Neural Architecture Search

ICCV

Fast and Practical Neural Architecture Search

ICCV

Teacher Guided Architecture Search

ICCV

AutoDispNet: Improving Disparity Estimation With AutoML

ICCV

Resource Constrained Neural Network Architecture Search: Will a Submodularity Assumption Help?

ICCV

One-Shot Neural Architecture Search via Self-Evaluated Template Network

ICCV

Evolving Space-Time Neural Architectures for Videos

ICCV

AutoGAN: Neural Architecture Search for Generative Adversarial Networks

ICCV

Discovering Neural Wirings

NeurIPS

Towards modular and programmable architecture search

NeurIPS

Network Pruning via Transformable Architecture Search

NeurIPS

Deep Active Learning with a NeuralArchitecture Search

NeurIPS

DetNAS: Backbone Search for Object Detection

NeurIPS

SpArSe: Sparse Architecture Search for CNNs on Resource-Constrained Microcontrollers

NeurIPS

Efficient Forward Architecture Search

NeurIPS

XNAS: Neural Architecture Search with Expert Advice

NeurIPS

DARTS: Differentiable Architecture Search

ICLR

ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware

ICLR

Graph HyperNetworks for Neural Architecture Search

ICLR

Learnable Embedding Space for Efficient Neural Architecture Compression

ICLR

Efficient Multi-Objective Neural Architecture Search via Lamarckian Evolution

ICLR

SNAS: stochastic neural architecture search

ICLR

NetTailor: Tuning the Architecture, Not Just the Weights

CVPR

Searching for A Robust Neural Architecture in Four GPU Hours

CVPR

ChamNet: Towards Efficient Network Design through Platform-Aware Model Adaptation

CVPR

Partial Order Pruning: for Best Speed/Accuracy Trade-off in Neural Architecture Search

CVPR

FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search

CVPR

RENAS: Reinforced Evolutionary Neural Architecture Search

CVPR

Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation

CVPR

MnasNet: Platform-Aware Neural Architecture Search for Mobile

CVPR

MFAS: Multimodal Fusion Architecture Search

CVPR

A Neurobiological Evaluation Metric for Neural Network Model Search

CVPR

Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells

CVPR

Customizable Architecture Search for Semantic Segmentation

CVPR

Regularized Evolution for Image Classifier Architecture Search

AAAI

The Evolved Transformer

ICML

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

ICML

NAS-Bench-101: Towards Reproducible Neural Architecture Search

ICML

On Network Design Spaces for Visual Recognition

ICCV

Towards Automatically-Tuned Deep Neural Networks

BOOK

NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications

ECCV

Efficient Architecture Search by Network Transformation

AAAI

Learning Transferable Architectures for Scalable Image Recognition

CVPR

N2N learning: Network to Network Compression via Policy Gradient Reinforcement Learning

ICLR

A Flexible Approach to Automated RNN Architecture Generation

ICLR

Practical Block-wise Neural Network Architecture Generation

CVPR

Path-Level Network Transformation for Efficient Architecture Search

ICML

Hierarchical Representations for Efficient Architecture Search

ICLR

Understanding and Simplifying One-Shot Architecture Search

ICML

SMASH: One-Shot Model Architecture Search through HyperNetworks

ICLR

Neural Architecture Optimization

NeurIPS

Searching for efficient multi-scale architectures for dense image prediction

NeurIPS

Progressive Neural Architecture Search

ECCV

Neural Architecture Search with Bayesian Optimisation and Optimal Transport

NeurIPS

Differentiable Neural Network Architecture Search

ICLR-W

Accelerating Neural Architecture Search using Performance Prediction

ICLR-W

Neural Architecture Search with Reinforcement Learning

ICLR

Designing Neural Network Architectures using Reinforcement Learning

ICLR

Neural Optimizer Search with Reinforcement Learning

ICML

Learning Curve Prediction with Bayesian Neural Networks

ICLR

Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization

ICLR

Hyperparameter Optimization: A Spectral Approach

NeurIPS-W

Speeding up Automatic Hyperparameter Optimization of Deep Neural Networksby Extrapolation of Learning Curves

IJCAI

NSGA-NET: A Multi-Objective Genetic Algorithm for Neural Architecture Search

Training Frankenstein’s Creature to Stack: HyperTree Architecture Search

Population Based Training of Neural Networks

GitHub

EmotionNAS: Two-stream Architecture Search for Speech Emotion Recognition

U-Boost NAS: Utilization-Boosted Differentiable Neural Architecture Search

Github

A Comprehensive Survey of Neural Architecture Search: Challenges and Solutions

ACM Computing Surveys

Automated Machine Learning on Graphs: A Survey

ICLR-W

On Hyperparameter Optimization of Machine Learning Algorithms: Theory and Practice

Neurocomputing

AutonoML: Towards an Integrated Framework for Autonomous Machine Learning

arXiv

Automated Machine Learning

Springer Book

Neural architecture search: A survey

JMLR

AutoML: A Survey of the State-of-the-Art

arXiv

A Survey on Neural Architecture Search

arXiv

Taking human out of learning applications: A survey on automated machine learning

arXiv

IoT Data Analytics in Dynamic Environments: From An Automated Machine Learning Perspective

Engineering Applications of Artificial Intelligence