SOTAVerified

AutoML

Automated Machine Learning (AutoML) is a general concept which covers diverse techniques for automated model learning including automatic data preprocessing, architecture search, and model selection. Source: Evaluating recommender systems for AI-driven data science (1905.09205)

Source: CHOPT : Automated Hyperparameter Optimization Framework for Cloud-Based Machine Learning Platforms

Papers

Showing 141150 of 641 papers

TitleStatusHype
Loss Function Search for Face RecognitionCode1
GAMA: a General Automated Machine learning AssistantCode1
AutoGAN-Distiller: Searching to Compress Generative Adversarial NetworksCode1
Neural Ensemble Search for Uncertainty Estimation and Dataset ShiftCode1
Does Unsupervised Architecture Representation Learning Help Neural Architecture Search?Code1
Efficient AutoML Pipeline Search with Matrix and Tensor FactorizationCode1
AutoML Segmentation for 3D Medical Image Data: Contribution to the MSD Challenge 2018Code1
Noisy Differentiable Architecture SearchCode1
DriveML: An R Package for Driverless Machine LearningCode1
Lite Transformer with Long-Short Range AttentionCode1
Show:102550
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1marc.boulleRank (AutoML5)6.4Unverified
2reference_mbRank (AutoML5)5.2Unverified
3postech.mlg_exbrainRank (AutoML5)5.2Unverified
4abhishek4Rank (AutoML5)4.6Unverified
5referenceRank (AutoML5)4.4Unverified
6reference_lsRank (AutoML5)4Unverified
7djajeticRank (AutoML5)3Unverified
8aad_freiburgRank (AutoML5)1.6Unverified
#ModelMetricClaimedVerifiedStatus
1Logistic RegressionAccuracy97.02Unverified
#ModelMetricClaimedVerifiedStatus
1Zero-shot-BERT-SORT1:1 Accuracy55Unverified
#ModelMetricClaimedVerifiedStatus
1Logistic Regressionaccuracy98.33Unverified