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 331340 of 641 papers

TitleStatusHype
AutoDES: AutoML Pipeline Generation of Classification with Dynamic Ensemble Strategy Selection0
Transformers Can Do Bayesian InferenceCode1
Evaluating Generic Auto-ML Tools for Computational Pathology0
Manas: Mining Software Repositories to Assist AutoMLCode0
Pipeline Combinators for Gradual AutoML0
Naive Automated Machine LearningCode1
Fast and Informative Model Selection using Learning Curve Cross-ValidationCode0
Diagnosis of sickle cell anemia using AutoML on UV-Vis absorbance spectroscopy data0
AutoDC: Automated data-centric processingCode1
DIVA: Dataset Derivative of a Learning Task0
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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